bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gut Microbiome Dynamics and Associations with Mortality in Critically Ill Patients
Authors: Salameh Tarik J. , Roth Katharine , Schultz Lisa , Ma Zhexi , Bonavia Anthony S. , Broach James R. , Hu Bin , Howrylak Judie A. 
Published: September 2022

Abstract
Background
Critical illness and care within the intensive care unit (ICU) leads to profound changes in the composition of the gut microbiome. The impact of such changes on the patients and their subsequent disease course remains uncertain. We hypothesized that specific changes in the gut microbiome would be more harmful than others, leading to increased mortality in critically ill patients.
Methods
This was a prospective cohort study of critically ill adults in the ICU. We obtained rectal swabs from 52 patients and assessed the composition the gut microbiome using 16S rRNA gene sequencing. We followed patients throughout their ICU course and evaluated their mortality rate at 28 days following admission to the ICU. We used selbal, a machine learning method, to identify the balance of microbial taxa most closely associated with 28-day mortality.
Results
We found that a proportional ratio of four taxa could be used to distinguish patients with a higher risk of mortality from patients with a lower risk of mortality (p = 0.02). We named this binarized ratio our microbiome mortality index (MMI). Patients with a high MMI had a higher 28-day mortality compared to those with a low MMI (hazard ratio, 2.2, 95% confidence interval 1.1-4.3), and remained significant after adjustment for other ICU mortality predictors, including the presence of the acute respiratory distress syndrome (ARDS) and the Acute Physiology and Chronic Health Evaluation (APACHE II) score (hazard ratio, 2.5, 95% confidence interval 1.4-4.7). High mortality was driven by taxa from the Anaerococcus (genus) and Enterobacteriaceae(family), while lower mortality was driven by Parasutterella and Campylobacter(genera).
Conclusions
Dysbiosis in the gut of critically ill patients is an independent risk factor for increased mortality at 28 days after adjustment for clinically significant confounders. Gut dysbiosis may represent a potential therapeutic target for future ICU interventions.
Basilar invagination without atlantoaxial dislocation: treatment by correction of clivus canal angle with interfacet distraction and fixation
Authors: Hou Zhe , Fan Tao , Fan Wayne , Jian Qiang , Wang Yinqian 
Published: September 2022

Abstract
Objective
Reports on the surgical technique used and clinical outcomes obtained during the treatment of basilar invagination (BI) without atlantoaxial dislocation (AAD) through the correction of the clivus canal angle (CCA) using interfacet distraction and fixation.
Methods
Nineteen cases with BI without AAD treated by the correction of the clivus canal angle were retrospectively analyzed. Pre- and postoperative computed tomography scans and three-dimensional reconstruction views were obtained to measure the size of the CCA, pB-C2 distance, and degree of BI. Chiari malformation and syringomyelia were evaluated by magnetic resonance imaging (MRI). The clinical outcomes for all patients were measured using the Japanese Orthopedic Association (JOA) scale. The CCA was corrected by using interfacet distraction and fixation techniques. Paired t-tests were used to compare pre- and postoperative measurements.
Results
All the patients were followed up for 12 to 36 months; no patient suffered intraoperative nerve or vascular injury. Clinical symptoms improved in 17 patients (89.5%). The mean JOA score increased from 12.32 ± 1.89 to 14.37 ± 1.30 (Z = -3.655, P < 0.001). The mean CCA improved from 129.34 ± 8.52° preoperatively to 139.75 ± 8.86° postoperatively (Z = -3.824, P < 0.001). The mean pB-C2 decreased from 7.47 ± 2.21 to 5.68 ± 3.13 (Z = -3.060, P = 0.002). Syringomyelia was significantly reduced in 10 out of 13 patients by the first follow-up year. All patients achieved bony fusion.
Conclusions
Posterior interfacet distraction and fixation to correct the CCA is a feasible and effective method for treating BI without AAD.
Over expression of recombinant Staphylokinase and reduction of inclusion bodies using IPTG as inducer in E. coli BL21 DE3
Authors: Muttar Barakat Abdul Razzaq , Panchal Rakesh Kumar R. 
Published: September 2022

Abstract
A previous research and studies have established the significance of describing Staphylokinase as a thrombolytic treatment, particularly in patients with cardiovascular disease, stroke, and other life-threatening disorders. Staphylokinase plays a significant part in the coagulation process through formation plasmin-Staphylokinase complex on the surface of the clot which activates plasminogen is generated by some strains of Staphylococcus aureus. The publication described the use of the E. coli strain BL12DE3 to produce the protein via the pET21a transporter is predicated on the use of a chemical stimulator (IPTG) which plays an important role in regulating protein recombinant by stimulating protein synthesis. Strain BL12DE3 activates T7 polymerase, encoding LacI via the pET21a transporter. It has been demonstrated that the IPTG inducer achieves the maximum level of protein expression in the shortest amount of time. A Staphylokinase was generated as a soluble protein in excess of 45 % by SDS-PAGE and subsequently purified by chromatography.
SSD with Multi-scale feature Fusion and Attention mechanism
Authors: Zeng Zhigao , Dong Lijun , Liu Qiang , Zhu Wenqiu , Zhu Yanhui , Meng Chen 
Published: September 2022

Abstract
In the Internet of Things, image acquisition equipment is very important, which will generate lots of invalid data when monitoring in real time. Analyzing the data collected from the terminal directly by edge calculation can remove invalid frames and improve the accuracy of system detection. SSD algorithm model is relatively light and fast detection speed. However, SSD algorithms don't take full advantage of both shallow and deep information, a multiscale feature fusion attention mechanism structure based on SSD algorithm was proposed in this paper, which combines the idea of multiscale feature fusion and attention mechanism. Improve the feature information expression ability by fusing adjacent feature layers for each detection layer. Then, add the attention mechanism to to improve the algorithm's attention to the feature map channels. The results of the experiment show that the optimized model detection accuracy is improved, which will greatly improve the reliability of edge calculation.
Giant Perianal Tumour Arising from Condyloma Acuminatum in a Patient Living with HIV-1
Authors: Liu Xiang , Zhu Xueling , Wan Zhikai , Lang Guanjing , Huang Ying , Zhu Biao 
Published: September 2022

Abstract
Background
Perianal cancer is a relatively rare disease, but it is prevalent in men who have sex with men and in patients who are positive for human immunodeficiency virus (HIV). Here, we report a case of a massive anal squamous cell carcinoma that measured 19 cm in length and 10 cm in diameter in a male patient living with HIV.
Case presentation
A 28-year-old man with a 5-year history of peri-anal condyloma acuminatum developed a rapidly enlarging mass in the anal region since the past few months. He had both HIV and syphilis infection, but never sought further treatment. Pathological analysis and immunohistochemistry confirmed squamous cell carcinoma with high-risk HPV infection. After multi-disciplinary treatment, albumin-paclitaxel combined with anti-programmed cell death protein 1 therapy and simultaneous antiretroviral therapy was initiated. The mass began to shrink after chemotherapy, but this did not prevent tumor progression. He eventually died from tumor-cachexia.
Conclusion
Early screening and treatment of perianal disease can help prevent progression to invasive anal carcinoma in high-risk groups such as men who have sex with men and immunosuppressed patients.
Brain MRI Segmentation Binary U-Net Based Architecture using Deep learning algorithm
Authors: B Nageshwar Rao , Re D.Lakshmi Sreenivasa , Gujja Harish 
Published: September 2022

Abstract
In medical image processing, Brain tumor segmentation is one of the most important tasks because the segmented region is helpful for the diagnosis and treatment of a disease. In any region, Gliomas may appear and they can be in any shape and size, which is helpful for automatic detection due to segmentation. One of the most evident tools of image processing is to provide complete information about brain tumor anatomy and makes an effective diagnosis through magnetic resonance imaging (MRI). To replace the manual detection system MRI is essential. Kaggle dataset proposed a brain tumor segmentation and detection system. To handle the task of segmentation of glioma, MRI scan based Binary U-Net-based deep learning model is proposed. By using this Binary U-Net Architecture, it identifies the boundary region of the tumor, which is present in the dataset. It detects the type of tumor present in the assigned dataset. This tumor detection is done by masking the original image and binary prediction is done internally by processing through skull removal, feature extraction, and multiple iterations. The binary prediction is compared with the human prediction, if it meets the pixel length, the model is saved and the glioma mask is predicted, else it is returned to data processing. From Binary prediction, some of the parameters are calculated based on the overlap of the segmentation region and pixels between the ground truth and predicted segmentation. Where Sensitivity, Dice, and Sensitivity metrics measure the overlap of pixels and Dice similarity coefficient (DSC) measures the overlap of segmentation region. Compare to previous techniques, Binary U-Net has Recall and Precision rises by 1.07 percent and 1.04 percent once residual dense blocks are included. As a result, residual dense blocks aid in the stabilization of the deep network and the integration of global features.
Occurrence of Onchocerciasis infection after decades of mass drug administration in the Western North Region of Ghana: The case of Sefwi Akontombra district
Authors: Mensah Derrick Adu , Debrah Linda Batsa , Boateng John , Ahiadorme Monica , Osei-Mensah Jubin , Opoku Vera Serwaa , Obeng Michael Agyemang , Kuutiero Eunice Kyaakyile , Opoku John , Rahamani Abu Abudu , Amponsem Sarfowaa , Obeng Prince , Gyasi Charles , Kutu Emmanuel Donawugube , Debrah Alexander Yaw 
Published: September 2022

Abstract
Background
Onchocerciasis is the world’s second leading cause of infectious blindness and a major public health problem in many parts of the world, including Ghana, with severe impact on the skin also. Mass drug administration (MDA) with ivermectin began in the Sefwi Akontombra district of the Western North Region of Ghana in 1994. The aim of this cross-sectional study was to evaluate the impact of about three decades of MDA on onchocerciasis and its clinical manifestations by investigating the current nodule and microfilaria (MF) prevalence in the Sefwi Akontombra district using established protocols.
Methodology
This cross-sectional study had participants examined for signs of dermal/skin onchocerciasis and palpated, and those with ≥ 1 palpable sub-cutaneous nodule had skin snips taken from the left and right iliac crests for later parasitological (microfilariae) assessment. Logistic regression models were used to identify independent predictive and risk factors significantly associated with nodule and MF prevalence.
Results
A total of 1980 participants from 25 communities in three sub-districts were recruited. Compliance to the MDA intervention in the district was 93.7%. The study recorded Onchocerca nodule prevalence of 35.4% (N = 701), out of which 31.5% (N = 221) were MF positives, with district community microfilariae load (CMFL) and geometric mean intensity of 0.25 MF/ss and 0.26 MF/ss respectively. Adawu, the central community among the 25 surveyed recorded the highest CMFL (0.77 MF/ss)— with 14 communities being hypoendemic and 11, mesoendemic for the onchocerciasis infection. The overall estimated district onchocerciasis MF prevalence was 11.2%, making the district hypoendemic. Of the 17 participants who presented with dermal symptoms, acute papular onchodermatitis (41.2%) was the most prevalent. Age, ivermectin intake and gender were the independent predictive factors significantly associated (p < 0.05) with onchocerciasis in the district.
Conclusion
Despite decades of ivermectin administration in the district, the MF prevalence in the district was > the 1% threshold required for elimination. As the focus of the Ghana Onchocerciasis Control Programme has changed from control to elimination, MDA should be intensified in areas with MF prevalence > 1%. Though the district’s CMFL was far below the 5.0 MF/ss public health problem threshold, macrofilaricidal drugs should be explored to complement the microfilaricidal ivermectin.
An NLP-Assisted Bayesian Time Series Analysis for Prevalence of Twitter Cyberbullying During the COVID-19 Pandemic
Authors: Perez Christopher , Karmakar Sayar 
Published: September 2022

Abstract
COVID-19 has brought about many changes in social dynamics. Stay-at-home orders and disruptions in school teaching can influence bullying behavior in-person and online, both of which leading to negative outcomes in victims. To study cyberbullying specifically, 1 million tweets containing keywords associated with abuse were collected from the beginning of 2019 to the end of 2021 with the Twitter API search endpoint. A natural language processing model pre-trained on a Twitter corpus generated probabilities for the tweets being offensive and hateful. To overcome limitations of sampling, data was also collected using the count endpoint. The fraction of tweets from a given daily sample marked as abusive is multiplied to the number reported by the count endpoint. Once these adjusted counts are assembled, a Bayesian autoregressive Poisson model allows one to study the mean trend and lag functions of the data and how they vary over time. The results reveal strong weekly and yearly seasonality in hateful speech but with slight differences across years that may be attributed to COVID-19.
A modified Conveyor-belt Algorithm to solve the critical section problem
Authors: Chanda Nilanjan 
Published: September 2022

Abstract
In the domain of Operating System, critical problem and its related concepts play an important role. Process Management is the most vital part for executing various programs required where every process completes for CPU and may use some common variables and changes made to these variables in concurrent processing can produce undesirable results. In this paper, a different type of algorithm is proposed which deals effectively for solving the critical section problem. This algorithm is based on the working of a conveyor belt that a given set of processes shall circulate over the conveyor belt and any process should be able to execute their critical section when it is its turn while the other processes must continue to circulate, waiting for its turn to enter the critical section until all of them are executed.
In vivo and in vitro validation of powdery mildew resistance in garden pea genotypes
Authors: Rana Chanchal , Sharma Akhilesh , Rathour Rajeev , . Bansuli , Banyal Devinder Kumar , Sharma Parveen , Rana Ranbir Singh 
Published: September 2022

Abstract
Powdery mildew is one of the serious diseases of garden pea which causes a large number of yield losses. Genetic resistance is quite effective, being cost-effective and environment friendly than fungicide applications. In the present studies an initial attempt has been made to identify resistant genotypes against powdery mildew disease developed from hybridization followed by validation of the disease. The newly isolated 44 lines along with four checks were screened under natural and artificial conditions. Ten lines viz., SP7, SN-1, SN-6-1, SN-7-1, SN-2, SN-5-2, SN-6-2, SN-21 and SP-28-1 showed resistant reaction along with check Palam Sumool while 27 lines were identified as moderately resistant in comparison to susceptible check Azad P-1. Besides, six lines namely, SP-2, SP-5, SP-10, SP-24, SA-4 and SP-12-1 gave moderately susceptible reaction along with checks Pb-89 and Palam Priya. Only, SP-19 was categorized as susceptible. The high yielding lines SP-3, SP-6 and SP-22 showed moderately resistant reaction in both natural and artificial conditions. Validation of resistance using molecular markers revealed that neither the parental genotypes nor the progenies possess the er1 gene of JI1559. The er2 linked marker ScOPX-171700 was polymorphic between Palam Sumool and Palam Priya but the marker didn’t show polymorphism between er2 harboring line (JI2480). These results suggested that the lines showing resistance under field conditions may have some other genes or alleles for resistance and further confirmation is needed by developing mapping populations with specific gene or gene combinations.
What do medical students and their trainers understand by primary health care in South Africa? A qualitative study
Authors: Mabuza Langalibalele Honey , Moshabela Mosa 
Published: September 2022

Abstract
Background:

The definition of Primary Health Care (PHC) issued by the World Health Organisation in 1978 indicated that it is essential health care which should be made accessible to individuals and their communities, close to where they live and work. In 2010 Starfield introduced the four pillars of PHC: the patient’s first contact with healthcare, comprehensive care, coordinated care and continuous care. This study sought to explore what undergraduate (UG) medical students and their trainers understood by PHC in four South African medical schools.

Methods:

A qualitative study using the phenomenological design was conducted among undergraduate medical students and their trainers. The setting were four medical schools in South Africa (Sefako Makgatho Health Sciences University, Walter Sisulu University and the University of KwaZulu-Natal and the Witwatersrand University). A total of 27 in-depth interviews were conducted among the trainers and 16 focus group discussions among the students who were in their clinical years of training (MBChB 4–6). Interviews were digitally recorded and transcribed verbatim, followed by thematic data analysis using the MAXQDA 2020 (Analytics Pro) software.

Results:

Six themes emerged in the understanding of PHC among students and their trainers: PHC as the patient’s first contact with the healthcare system; comprehensive care; coordination of care and continuity of care. There was agreement between students and their trainers in these four themes. However, there was a difference of opinion on whether PHC was a level or an approach to healthcare and the role of specialist trainers PHC.

Conclusions:

There were areas of convergence and divergence in the understanding of PHC among the students and their trainers. Since understanding should be the basis for training, there is need for trainers and their students to seek common understanding of PHC.
Using random forest to find the discontinuity points for carbon efficiency during COVID-19
Authors: Qu Yingchi , Lim Ming K. , Yang Mei , Ni Du , Xiao Zhi 
Published: September 2022

Abstract
As there is a constant trade-off between carbon dioxide emissions against economic growth for every government, carbon efficiency is a key indicator to guide sustainable development. However, the energy crisis and COVID-19 recovery could affect carbon efficiency. Therefore, this paper combines the fuzzy regression discontinuity and random forest algorithm to estimate the discontinuity of the energy crisis and COVID-19 recovery on carbon efficiency. The results show that there are two cutoffs between carbon efficiency and coal prices. The positive treatment effect at cutoff 1 proves that the “zero-tolerance” policies effectively promote carbon efficiency. Besides, the negative treatment effect at cutoff 2 proves that electricity rationing has not always improved carbon efficiency during the energy crisis.
The Construction and Operational Models of Internet Hospitals in China: A Hospital-Based Survey Study
Authors: Chen Xuejiao , Wu Xinxia , Zhang Qihang , Jing Ran , Cheng Weibin , Tian Junzhang , Jin Changxiao 
Published: September 2022

Abstract
Background
China empowered and continues to empower internet hospitals, which saw an increase in their development due to the pandemic, to fight against COVID-19. The construction and operational models of internet hospitals can be categorized as self-constructed and self-managed models, self-constructed and enterprise-run models, hospital and enterprise joint-owned models, and as being hosted by a third-party platform. Despite the increasing importance of internet hospitals, there have been few systematic summaries of its construction and operational models.
Objective
The study’s primary purpose was to understand the construction and operational models of internet hospitals in China.
Methods
Data were collected from September 2020 from the internet hospital survey and hospital staff survey based on 39 medical institutions and 356 medical staff. T-tests were used to compare the continuous variables’ values. Chi-square tests were used to compare the proportions of the categorical variables. The self-perception of the internet hospitals’ services was assessed on 17 aspects using a 5-point Likert scale. A root cause analysis was used to identify the root causes and influencing factors of the current deficiencies faced by internet hospitals.
Results
Among the 39 internet hospitals, 22 (56.4%) were self-constructed and self-managed. Self-constructed and self-managed hospitals had lower percentages of professionals providing online services (P=0.006), numbers of doctors outside of the entity (P=0.006), numbers of online nurses (P=0.004), and ratio of online nurses to offline doctors as compared to other models of internet hospitals (P < 0.001). Among the 17 evaluation aspects of the medical staff’s self-perception of the internet hospitals’ services, fee transparency, fee rationality, travel cost capital, patience and responsibility, and consultation behaviors had the highest scores. The root causes included five aspects: human, channels, prices, services, and time.
Conclusions
There were differences between self-constructed and self-managed models and other models of internet hospitals. This study enriches the literature on the construction and operational models of internet hospitals and provides additional policy implications for tele-medicine management.