bluuebunny/crossref_metadata_2025_split huggingface dataset:
Preventive practices towards Sexually Transmitted Infection and its determinants among young people in Ethiopia: a protocol for a systematic review and Meta-analysis
Authors: Anbesu Etsay Woldu , Aychiluhm Setognal Birara , Alemayehu Mussie 
Published: August 2021

Abstract
Background: Globally, about 178.5 million new cases of curable sexually transmitted infections occur among young people aged 15-24 years. There are fragmented and inconsistent findings on preventive practices of sexually transmitted infection. Thus, this systematic review and meta-analysis aimed to estimate the pooled prevalence of preventive practices of sexually transmitted infection and identify its determinants among young people in Ethiopia. Methods: The Preferred Reporting Items for Systematic review and Meta-analyses (PRISMA) was employed to develop the review protocol. Databases such as PubMed, CINAH, Google, and Google Scholar were used to search published and unpublished studies. Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument will be used to assess the quality of the study. Statistical heterogeneity will be checked using I2 statistics. Subgroup analyses and meta-regression will be done to identify the sources of heterogeneity. The statistical analysis will be done using STATA version-14 software. A random-effects model will be employed to estimate the pooled prevalence and identify determinants of preventive practices of sexually transmitted infections. Discussion: Young people have a high unmet need for sexual and reproductive health services and poor preventive practices toward sexually transmitted infection. Although there are studies on the sexually transmitted infection preventive practice, there is no study finding on the pooled prevalence of the preventive practices of sexually transmitted infection and its determinants among young people in Ethiopia. Thus, this systematic review and meta-analysis will help to develop appropriate interventions.
Development of Molecular Markers Linked To QTL/Genes Controlling ZN Efficiency
Authors: PINAR Hasan , Bulbul Cansu , Simsek Duran , Shams Mostafakamal , Mutlu Nedim , Ercisli Sezai 
Published: August 2021

Abstract
Zinc (Zn) deficiency is a widespread problem in reducing the yield and quality of crop plants worldwide. It is important to utilize molecular markers linked to Zn efficiency to develop high Zn efficient cultivars in pepper (Capsicum annuum L.). We constructed a genetic map using an F2 populations derived from C. annuum L. (Alata 21A) X C. frutescens L. (PI 281420) cross. The QTLs for Zn efficiency were mapped using F2:3 population. A genetic map with 929,6 cM in length and 12 linkage groups were obtained using 62 markers (31 SRAP, 19 SSR and 11 RAPD). The 41 linked QTLs related with nine (9) Zn efficiency characters were mapped on linkage groups. Results suggest that selecting plants for tolerance to Zn deficiency are expected to be rather responsive among segregating populations for breeding and developing Zn efficient genotypes in pepper. The molecular markers are expected to aid selection and expedite breeding peppers resistant to Zn deficiency in soils low for available Zn contents.
Prevalence of Electrocardiographic Abnormalities Among People Living With HIV/AIDS in Sub-saharan Africa: Protocol for a Systematic Review and Meta-analysis
Authors: Semulimi Andrew Weil M , Kyazze Andrew Peter , Mukisa John , Batte Charles , Bongomin Felix 
Published: August 2021

Abstract
IntroductionElectrocardiographic (ECG) abnormalities are highly prevalent among people living with HIV/AIDS (PLWHA) contributing to the rising burden of cardiovascular diseases among this population. Sub-Saharan Africa (SSA) contributes more than two thirds to the global burden of HIV/AIDS. However, an accurate account of the prevalence of ECG abnormalities in SSA is unknown. This study aims to determine the prevalence of ECG abnormalities among PLWHA in Sub-Saharan Africa. Methods and analysisA systematic review and meta-analysis will be conducted. Databases including EMBASE, MEDLINE, African Journal Online and The Cochrane Library (Cochrane Central Register of Controlled Trials (CENTRAL), and Cochrane Methodology Register) will be used to search for studies published between 1st January 2000 and 31st December 2020. Studies reporting any form of ECG abnormalities will be considered. Additionally, articles in both English and French will be reviewed. Articles will be screened and reviewed by two independent reviewers to determine their eligibility and any disagreement will be resolved through discussions with fourth and fifth reviewer. Eligibility of the studies will be assessed and judged based on the pre-set criteria. Retrieved studies will be assessed for validity using the Cochrane risk of bias tool and the modified Newcastle Ottawa Scale by two reviewers. Analysis of proportions will be done using STATA MP Version 16.0. A p<0.05 will be considered statistically significant.DiscussionIn the face of a growing burden of cardiovascular diseases among PLWHA, this study will provide an estimate of ECG abnormalities among PLWHA which will emphasize the importance of ECGs in screening for cardiovascular diseases in this population.Systematic review registration numberCRD42021243664.
Longitudinal increase of CSF soluble TREM2 is driven by early aggregation of Aβ42 and associates with slower amyloid deposition and clinical decline in autosomal-dominant Alzheimer’s disease
Authors: Haass Christian , Morenas-Rodriguez Estrella , Li Yan , Nuscher Brigitte , Franzmeier Nicolai , Xiong Chengjie , Suárez-Calvet Marc , Fagan Anne , Schultz Stephanie , Gordon Brian , Benzinger Tammie , Hassenstab Jason , McDade Eric , Feederle Regina , Karch Celeste , Schlepckow Kai , Morris John , Kleinberger Gernot , Nellgård Bengt , Vöglein Jonathan , Blennow Kaj , Zetterberg Henrik , Ewers Michael , Jucker Mathias , Levin Johannes , Bateman Randall 
Published: July 2021

Abstract
Therapeutic modulation of TREM2-dependent microglial function provides an additional strategy to slow progression of Alzheimer disease (AD). Although studies on animal models suggest that TREM2 is protective, the trigger of increased TREM2 expression during disease progression and its clinical and pathological consequences in AD remain unclear. We measured longitudinally soluble TREM2 (sTREM2) as a surrogate marker for protective TREM2-signalling in cerebrospinal fluid (CSF) from participants in the Dominantly Inherited Alzheimer Network (DIAN) observational study. In mutation carriers (MC), the longitudinal sTREM2 increase followed the earliest aggregation of Aβ42 captured by CSF-Aβ42 decrease, but not yet by Pittsburg compound-B Positron Emission Tomography (PiB-PET). Higher sTREM2 increase rates provided protection from Aβ-deposition, whereas lower rates enhanced p-tau increase associated with PiB-PET increase. Moreover, presymptomatic MC with high or low sTREM2 increase rates have opposite associations between CSF Aβ42 and PiB-PET longitudinal changes, suggesting that TREM2 modifies Aβ plaque deposition and compaction. Finally, higher sTREM2 increase rates protected from cortical shrinkage and cognitive decline. Our findings position the TREM2 response within the amyloid cascade right after the first pathological changes in Aβ42 aggregation, support ongoing efforts to develop TREM2 modulating therapies, and predict a very early window for therapeutic intervention.
Real-Time Slurry Characteristic Analysis During Ball Milling Using Vibration Data
Authors: Jeong Hyeondeok , Yu Jungwon , Lee Youngjae , Lee Sung-min , Ryu Sung-Soo , Kim Seiki 
Published: August 2021

Abstract
The characteristics of an internal slurry were analyzed during ball milling, which is commonly utilized in ceramic processing. We used a device with a capacity of 50 L because this is the size employed in industries, and built a circulation system to collect the slurry during the milling process. The properties of the slurry were characterized in terms of their particle size and viscosity, while vibration data were collected from the side of the ball mill drum in real time. A fast Fourier transform was performed on the vibration data, allowing the energy to be calculated and compared with the slurry characteristics. The vibration data in the 3–4 kHz range showed a strong negative correlation with the slurry viscosity. Our results confirm that the characteristics of the internal slurry can be monitored in real time using vibration data collected during ball milling.
Infection Age as a Predictor of Epidemiological Metrics for Malaria
Authors: Henry John M , Carter Austin , Smith David L 
Published: August 2021

Abstract
Background Accurate estimation of the burden of Plasmodium falciparum is essential for strategic planning for control and elimination. Due in part to the extreme heterogeneity in malaria exposure, immunity, other causes of disease, direct measurements of fever and disease attributable to malaria can be difficult. This can make a comparison of epidemiological metrics both within and between populations hard to interpret. An essential part of untangling this is an understanding of the complex time-course of malaria infections.Methods We reanalyzed malaria therapy infections in which individuals were intentionally infected with malaria parasites. In this analysis, we examined the age of an infection as a covariate describing aggregate patterns across all infections. We performed a series of piecewise linear and generalized linear regressions to highlight the infection age dependent patterns in both parasitemia and gametocytemia, and from parasitemia and gametocytemia to fever and transmission probabilities, respectively. Results The observed duration of untreated patent infection was 130 days. As infections progressed, the fraction of infections subpatent by microscopy increased steadily. The time-averaged malaria infections had three distinct phases in parasitemia: a growth phase for the first 6 days of patency, a rapid decline from day 6 to day 18, and a slowly declining chronic phase for the remaining duration of the infection. During the growth phase, parasite densities increased sharply to a peak. Densities sharply decline for a short period of time after the peak. During the chronic phase, infections declined steadily as infections age. Gametocytemia was strongly correlated with lagged asexual parasitemia. Fever rates and transmission efficiency were strongly correlated with parasitemia and gametocytemia. The comparison between raw data and prediction from the age of infection has good qualitative agreement across all quantities of interest for predicting averaged effects. Conclusion We established age of infection as a potentially useful covariate for malaria epidemiology. Infection age can be estimated given a history of exposure; accounting for exposure history may potentially provide a new way to estimate malaria-attributable fever rates, transmission efficiency, patent fraction, and more in immunologically naïve individuals such as children and people in low-transmission regions. Understanding how immune responses modify these statistical relationships is key for being able to apply these results more broadly.
Application of Artificial Intelligence in a Real-World Research for Predicting the Risk of Liver Metastasis in T1 Colorectal Cancer
Authors: Han Tenghui , Zhu Jun , Xu Dong , Chen Rujie , Wang Shuai , Chen Xiaoping , Zheng Jianyong , Xu Chunsheng 
Published: August 2021

Abstract
Background: The liver is the most common metastatic site of colorectal cancer (CRC) and liver metastasis (LM) determines subsequent treatment as well as prognosis of patients, especially in T1 patients. T1 CRC patients with LM are recommended to adopt surgery and systematic treatments rather than endoscopic therapy alone. However, there is still no effective model to predict the risk of LM in T1 CRC patients and we aim to develop a novel and accurate predictive model.Methods: We integrated two independent CRC cohorts from Surveillance Epidemiology and End Results database (SEER) and Xijing hospital. Artificial intelligence (AI) and machine learning methods were adopted to establish the predictive model.Results: A total of 16785 and 326 T1 CRC patients from SEER database and our hospital were incorporated respectively in the study. We found that age, gender, married status, primary site, tumor size, carcinoembryonic antigen (CEA), tumor type, grade, N stage and perineural invasion were significant independent factors for predicting the presence of LM, among which tumor size is the most important. The stacking bagging model showed the best predictive capability, achieving a sensitivity of 0.8452, a specificity of 0.9566, and an area under the curve of 0.9631. In addition, the stacking model had an excellent discriminative ability and accurately screened out eight LM cases from 326 T1 patients in the outer validation cohort. Ultimately, we authenticated the prognostic value of the stacking model, which is consistent with the predictive result of LM.Conclusion: We successfully established an innovative and convenient AI model for predicting LM in T1 CRC patients, which was further verified in our dataset.
Comparison of Two Predictive Models of Sepsis in Critically Ill Patients Based on the Combined use of Inflammatory Markers
Authors: Li Xiaoming , Liu Chao , Wang Xiaoli , Mao Zhi , Yi Hongyu , Zhou Feihu 
Published: August 2021

Abstract
Background: Sepsis is considered to be a systemic inflammatory response due to infection, resulting in organ dysfunction. Timely targeted interventions can reduce mortality and improve prognosis. Therefore, it is important to identify potential sepsis in time. Inflammation plays a crucial role in the process of sepsis. We combined inflammatory markers to develop and validate a nomogram model and a simple risk scoring model for predicting sepsis in critically ill patients. Furthermore, comparing the prediction performance of the two models.Methods: The medical records of adult patients admitted to our intensive care unit (ICU) from August 2017 to December 2020 were analyzed. The finally included patients were randomly divided into training cohort (70%) and validation cohort (30%). A nomogram model for sepsis was developed through multivariate logistic regression analysis in the training cohort. The continuous variables included in nomogram model were transformed into dichotomous variables. Then a multivariable logistic regression analysis was performed based on these dichotomous variables and the odds ratio (OR) for each variable was used to construct a simple risk scoring model for predicting sepsis. The receiver operating characteristic curves (ROC) were constructed and the area under the curve (AUC) was calculated to evaluate the discrimination performance of the two models. Results: According to our inclusion and exclusion criteria, 2074 patients were included in study. Finally, white blood cell (WBC), C-reactive protein (CRP), interleukin-6 (IL-6), procalcitonin (PCT) and neutrophil-to-lymphocyte ratio (NLR) were included in our models. The AUC of the nomogram model was 0.854 (95%CI: 0.835-0.872). The AUC of the simple risk scoring model was 0.842 (95%CI: 0.822-0.861). When the cut-off value was 7.5 points, the sensitivity was 77.03% and the specificity was 75.75%. The prediction performance of the two models on sepsis is comparable (p=0.1298) and better than that of Sequential Organ Failure Assessment (SOFA) scores (AUC=0.759).Conclusions: This study combining five commonly available inflammatory markers (WBC, CRP, IL-6, PCT and NLR) developed a nomogram model and a simple risk scoring model to predict sepsis in critically ill patients. Although the prediction performance of the two models is comparable, the simple risk scoring model may be simpler and more practical for clinicians to identify potential sepsis in critically ill patients at an early stage and make treatment strategies.
Comprehensive histological imaging of native microbiota in human glioma
Authors: Zhao Jiajia , He Dian , Lai Hei Ming , Xu Yingying , Luo Yunhao , Li Ting , Liang Jianhao , Yang Xiaodu , Guo Linlang , Ke Yiquan , Zhou Hongwei , Wu Wu-Tian , Guo Hongbo , Sun Haitao 
Published: July 2021

Abstract
Mounting evidence suggests that distinct microbial communities reside in tumors and play important roles in tumor physiology. Recently, Nejman et al. profiled the composition and localization of intratumoral bacteria using 16S DNA sequencing and histological visualization methods across seven tumor types, including human glioblastoma. However, considering potential contamination in their sample origins and processing, the results based on traditional histological methods need to be validated. Here, we propose a three-dimensional (3D) intratumoral microbiota visualization and quantification protocol to observe microbiota in intact tumor tissues on the premise of avoiding possible contamination in the surface of tissues, based on tissue clearing, immunofluorescent labeling, microscopy imaging, and image processing. For the first time, we have achieved 3D quantitative imaging of bacterial LPS fluorescent signals deep in gliomas in a contamination-free manner, which was founded mostly localized near nuclear membranes or in the intercellular space. Through an automated statistical algorithm, reliable signals can be distinguished for further analysis of their sizes, distribution, and fluorescence intensities. Combining two-dimensional images from multiple thin-section histological methods, including immunochemistry and fluorescence in situ hybridization, we provide a comprehensive histological investigation of the morphology and distribution of these signals on human glioma samples. We expect that this multi-evidence chain will provide supporting proof for the presence of intratumoral bacteria in human glioma and that the integrated pipeline can be applied to investigate the native bacteria within diverse tumors and contribute to the interpretation of their direct roles in the tumor microenvironment.
Public Adherence to Preventive Practices during the Third Wave of the COVID-19 in Afghanistan
Authors: Nemat Arash , Sediqi Mohammad Faiq , Elhadi Yasir Ahmad Mohammed , Essar Mohammad Yasir , Raufi Nahid , Asady Abdullah 
Published: August 2021

Abstract
Background

The COVID-19 pandemic emerged from Wuhan, China and has spread across the world and raised public health concerns. To curb the spread of the disease, the government has imposed prevention measures. The objective of this study was to examine the compliance of people with infection prevention practices during the third wave of the pandemic to provide an updated insight into the situation and help policy makers in designing effective measures.
Methods

This was an online survey of the general population in Afghanistan from April, 2021 to May, 2021. Non-probability convenience sampling technique was used to recruit the respondents. The target sample size was found to be around 1,094 respondents. Data collection was guided through self-administered questionnaire developed by the researchers according to the World Health Organization (WHO) guidelines.
Results

From 1,094 respondents, 78% were male. Majority of the respondents were aged ≤ 30 years and had an undergraduate education. Nearly, 1 in 3 participants were healthcare workers and 70% were living in households with 5 or more family members. Overall, 70% of the respondents reported good preventive practices. No significant association found between male and female participants with regard to preventive practices against the COVID-19. The frequency of good preventive practices was significantly higher in participants more than 30 years old (p = 0.035), people with a post-graduate education (p = 0.025), healthcare workers (p = 0.002), and households with less than five family members (p = 0.002).
Conclusion

Generally, the public in Afghanistan are following infection prevention rules. However, there are certain areas which require further improvement such as observing social distance and avoid shaking hands when meeting others. Negligence of these prevention practices can lead to the increase of infection transmission among people. Public awareness should be continued to keep the people supportive of the government policies. Social media, television advertisements, and similar platforms may be used for this purpose.
Analysis of discordance between AMH and AFC in IVF patients: a retrospective cohort study
Authors: Chen Yannan , Gu Xiaoling , Guan Xi , Yu Minyan , Zhong Shuping , Yang Panpan , Wang Xia , Wang Di 
Published: August 2021

Abstract
Background

Both anti-Mullerian hormone (AMH) and antral follicle count (AFC) predict ovarian reserve independently and have been shown to correlate well. However, it is quite common to encounter discordance between the two clinical indices. This objective of this study is to speculate which condition is favorable to patients and to decide what best to be done in cases of such discordance.
Methods

This retrospective cohort study analyzed the medical records of 714 women undergoing the first IVF cycle at the Center for Reproductive Medicine, the Affiliated Hospital of Nantong University, Nantong, Jiangsu between January 2017 and December 2020. All patients had their essential characteristics, baseline FSH, Estradiol, PRL, LH, Testosterone, CA125, AMH, and AFC recorded. Patients were classified into three groups according to whether their AMH and AFC values were in the lower quartile, upper quartile, or in between, namely Group A (Concordance, concordant in AMH and AFC), Group B (HTP, AMH concentration higher than predicted according to AFC) and Group C (LTP, AMH concentration lower than predicted according to AFC). SPSS 25.0 software package (SPSS, Inc., Chicago, IL, USA) was used for statistical analysis.
Results

The entire study population has a good concordance between AMH and AFC. 240 women (33.61%) had discordant AMH and AFC values, and the proportion in Group B(HTP) and Group C(LTP) seemed similar (16.67% VS 16.94%). The three cohorts had similar age, infertile duration, FSH, Estradiol, PRL, LH, Testosterone, and CA125 levels. BMI progressively increased from Group B to Group A and to Group C. The ratio of patients, who had completely mature oocytes (COM), rapidly decreased from Group C to Group A and to Group B. Although no significant difference in CMO rate was observed among Group A, B, and C when stratified according to BMI, CMO rate was the highest (72.31%) when BMI < 18.5 kg/m2 in all BMI categories.
Conclusions

Our analysis demonstrated a high frequency of clinical discordance between AMH and AFC in women undergoing IVF therapeutic regime. Patients’ BMI and completely mature oocytes ratio are significantly different among distinct grouping based on their AMH and AFC partition.