bluuebunny/crossref_metadata_2025 huggingface dataset:
Lessons Learned from 150 Jet-Type Perforate, Wash and Cement Well Abandonment Operations
Authors: Hovda Lars , Mueller Dan , Phadke Amal , Nevoey Harald , Gonuguntla Praveen
Published: February 2024

ConocoPhillips Scandinavia (COPSAS) uses the Jet-Type Perforate-Wash-Cement (P/W/C) technique as the primary method for well abandonment in the Greater Ekofisk Area (GEA) of the North Sea. The procedure used for the abandonment process was first published in 2020 (SPE-202397-MS), as was the complementary Computational Fluid Dynamics (CFD) results used to optimize the process (SPE-202441-MS). This paper will cover the most recent learnings and the latest CFD-based design modifications made to the bottom hole assembly (BHA) with the objective to achieve the best possible abandonment plug.
Application of Gamification Techniques in Well Control Training and Competency
Authors: Jensen J. W. , Kettler T. , Ozkan F.
Published: February 2024

Technological advances have rapidly expanded access to competency development and learning over the last decade in various contexts outside the oil and gas industry. Expanding access to the internet using portable devices with high computing power has transformed the way people learn globally. This research collects and expands on work done recently by the International Association of Oil and Gas Producers (IOGP) to advance the use of technology in well control training and competency retention. Experiences over the past five years illustrate that the necessity of remote learning during the COVID-19 pandemic has accelerated acceptance for hybrid (combined remote and in-person) learning methodologies in the oil and gas industry. Studies into gamification over the past two decades show it has a statistically significant positive effect on cognitive, motivational and attitudinal aspects of adult learning. Synergized learning combining remote and in-person education with gamified learning systems present an opportunity to improve competency development and sustainment. Applying these learnings to develop both existing and new computer-based aspects of well control training and competency sustainment programs could improve well control competencies across the industry, thus enhancing performance in the critical process safety activities of upstream oil and gas operations. This paper summarizes two industry reports on these topics, presents detailed analytical findings of academic research into gamification, and recommends how to implement hybrid learning and gamification strategies to improve vital well control training and competency sustainment for the oil and gas workforce.
First SAGD Well Placement Using Non-Stationary Definitive Dynamic Surveys Passive Magnetic Ranging and Gyro While Drilling
Authors: ElGizawy Mahmoud , Fraser Mark , Soh Azrin , Qalhati Asaad Al , Muqarshi Moosa Al , Bahri Salim Al , Musallami Ahmed Al , Mahrooqi Hamiyar S Al , Greenwell Nicholas , Lightfoot Jonathan
Published: February 2024

Drilling Steam Assisted Gravity Drainage SAGD wells requires placing the lateral section of the producer parallel to the lateral section of the steam injector and within a predefined distance to maximize production. After one well is drilled and completed, the second well is drilled using advanced wellbore positioning techniques to keep the two laterals at specific distance in close proximity to each other.

Active Magnetic Ranging is frequently used for positioning of SAGD wells, whereby an electromagnetic source, such as a solenoid is run on wireline in the first well that has been drilled and distance and direction measurements are made using the MWD tool while drilling in the second well. This increases the complexity of the operation as there is requirement to convey the source tool on wireline in a horizontal well and solutions for doing this, such as a tractor or coiled tubing, add considerable expense.

Passive Magnetic Ranging PMR is a common technique to estimate the distance and direction between the two wells while drilling the second well, without any requirement to run wireline tools in the offset wellbore. However, this technique requires taking at least 10 stationary surveys every stand if not more. This conventional practice leads to significant additional rig time and often increases directional drilling complexity from hole washouts to stuck pipe events. Additionally, as the wells are drilling into each other from opposite directions, both wells have high lateral and vertical uncertainty. The close proximity of both wells and the resultant external magnetic interference makes surveying an additional challenge to the BHA design and well integrity.

This is the first worldwide application of drilling SAGD twin wells utilizing Definitive Dynamic Surveys DDS to save two hours per stand by eliminating all the rig times taking stationary surveys every stand for PMR as well as eliminating all the risk to the drilling operation due to the prolonged time of having the drill string stationary. In addition, it is the first time to run a solid-state Gyroscopic Measurement While Drilling GMWD tool to measure the accurate wellbore position of the drilling well. This had significantly reduced the uncertainty of the estimated distance and direction between the two twinned wells.
Interpretation of Along-String-Measurements and Downhole Tool Data as a Solution for Intelligent Hole Cleaning in Real-Time
Authors: Chatar Crispin , Converset Julien , Sharma Sunil
Published: February 2024

The drilling industry is still plagued by challenges such as losses, packoff, hole-cleaning issues, and wellbore instability. Research and development using data from multiple sources have led to the development of an intelligent hole-cleaning answer product that can be used for a wellbore risk reduction service. The service would aim to optimize the rate of penetration through better understanding of hole cleaning. This digital solution that will enhance the well construction process by optimizing hole cleaning in real time. This solution is best delivered by using a combination of data and processes from multiple sources such as along-sting measurements (ASM), surface data, and downhole tools. There are several applications for this service such as land drilling, deepwater wells, horizontal wells, multilateral wells, highly deviated wells, and extended reach drilling.

The service uses a combination of technologies previously only available as separate services. The service uses ASM sensors to optimize hole cleaning. Calibration of the cutting pressure profile with a real-time simulator using a multipoint pressure measurement along the string is provided. In addition to ASM sensors, the weight and volume of the cuttings are continuously recorded at the flow lines and compared to theoretical data. As a result, mud rheology, wiper trips, and drilling parameters can be optimized, and hole-cleaning best practices can be refined. Stuck pipe, cuttings bed buildups, and wellbore instability can be detected and mitigated against, enabling safer drilling and minimization of nonproductive time. This paper will showcase how this can be done and what visualizations can be shown. It is intended to give a peak at the solution developed.
New Techniques for Intelligent Offset Data Analysis Using Artificial Intelligence
Authors: Sheth Prasham , Chatar Crispin
Published: February 2024

For well construction, planning is one of the most important phases in the delivery of a well. To select the right engineering solutions, it is important to analyze offset data. It is common for engineers to search, index, and catalog offset data. Today, as it has been historically for the industry, this is mostly a manual task. In the past few years, many advances in the way data have been collected, stored, and sorted have made the data easier to access, but actually determining which data are similar enough to use as offset data is still done manually. In simple cases, engineers draw a circle around the coordinates of the well to be drilled and any data within that circle would be considered offset data. This method considers only the geospatial similarity of the wells, and it is used because of time and technology constraints. In our work, we developed a method for a data-driven solution to this problem of identifying offset data.

Data are critical for producing digital products and services. More than 2 years of research have led to the implementation of a powerful tool that allows users to search all global data to discover similar attributes for oil and gas data. In addition, the method includes the ability for users to define importance or allocate priorities to various features in the data. The mentioned advances in collecting, storing, and sorting data have been a major enabler in the evolution of this technology.

This work introduces a developed framework that aids in identifying offset data by implementing a dynamic data-driven solution to analyze and display the similarity of the offset well data in a new way.
A Platform for Data Science and Analytics at the Edge
Authors: Godumagadda A. , Groh A. , Corne E. , Kasireddy P.
Published: February 2024

Increased digitalization in industry has brought forth a myriad of applications for data science and analytics over the past decade. As needs for advanced modeling and analytics have grown, this onshore drilling contractor embarked on a journey to centralize data acquisition, aggregation, transmission, and modeling into one platform located on-location.

This paper explains how the combination of both data exchange and modeling has allowed for the development of three novel controls applications that are combinations of traditional programming and industrial control logic. This opens doors to make advanced data science modeling, such as machine learning and online learning, available directly to existing rig control systems that do not have these capabilities.

The flexibility of this system offers significant opportunity for applying advanced analytics and data science tools at the rig site. Rig control systems are no longer limited by traditional industrial controllers but have the ability to interface with performance applications written in traditional programming languages. Applications running on our edge servers, integrated as input/output to the control systems, removes the limitations of the PLCs (programmable logic controllers) and allows us to "modernize" our control system without having to replace existing PLCs.
Novel Use of Dual-String Barrier Evaluation for an Efficient Well Sidetrack
Authors: Govil Amit , Alvenes Tina , Bose Sandip , Delabroy Laurent , Straume Martin , Zeroug Smaine , Ishberdina Gulnara
Published: February 2024

In oil wells, operators must prove the presence of a barrier behind multiple casings, which is expensive as they need to remove pipes and evaluate a single casing. To reduce cost and carbon emissions, we implemented a solution that involved logging through tubing to evaluate both the condition behind the tubing and the barrier behind the second pipe, while satisfying NORSOK D-10 guidelines for single-casing evaluation.

A combination of ultrasonic and sonic tools was deployed within the tubing. The ultrasonic measurements provide detailed understanding of the annular content behind/around the tubing versus depth along with position of tubing in the casing. The sonic measurements, with lower frequencies, have a greater depth of investigation and thereby evaluate the presence of any solids behind the second pipe. Extensive modeling and laboratory experiments of dual-string configurations in our research facility along with multiple sets of field data helped determination of the presence of solids using both ultrasonic and sonic measurements.

Two wells, a water injector, and an oil producer, were intervened via intervention tower in the Norwegian continental shelf (NCS). For the injector well (7-in. tubing and 9 5/8-in. casing), dual-string evaluation results were compared with the first bond log along with extended leakoff test. For the producer well (5 1/2-in. tubing and 9 5/8-in. casing), dual-string evaluation results were compared against a single-casing validation log. The validation log provides a strong degree of confidence in the dual-string evaluation results. Data from the dual-string evaluation and single-casing log will be used to generate a machine learning model for this well geometry, fluids, cement, and formation and is expected to give another high-resolution azimuthal prediction, which would allow for even higher confidence in the answers in later operations with the possible elimination of the need for a validation log.

This paper discusses an offshore case study where the technology was used in two wells in the NCS. The results and observations with dual-string logging technology will be presented in addition to the validation result after pulling the inner tubing. These dual-string log measurements were then used to streamline the sidetracking program, resulting in cost saving due to offline rig activity and minimizing contingency operation, rig time, and scope while reducing overall carbon emissions.
Revolutionizing Wellbore Intersections: Advancements in Coiled Tubing Ranging While Drilling Technology for Access-Independent Wellbore Intersects
Authors: Menard T. , Mehrotra A. , Rowcliffe N. , Moss C. , Moss F. , Rassadkin G.
Published: February 2024

Wellbore intersections are typically achieved using a conventional rotary drilling rig and wireline deployed magnetic ranging tools. Separate trips are made for each system in order to intersect a target wellbore. While this approach is often successful, it is time-consuming, resulting in more time spent on tripping than drilling. The extended trip times and the potential for well control vulnerabilities are issues that require attention. This paper introduces a novel solution to address these concerns.

The primary objective is to expedite wellbore intersections while improving process safety. The field-tested solution presented here involves the implementation of a coiled tubing ranging while drilling system, integrating electric current injection and sensor assembly into a single BHA with a live data connection to the surface. By eliminating separate wireline runs and reducing jointed pipe trip times, operations are significantly accelerated while dramatically improving key performance metrics. A high density of ranging data sets, averaging 3,800 samples per minute, was maintained during drilling. This method offers an efficient and safe alternative by combining multiple independent services at the wellsite into an end-to-end solution. Furthermore, the technology provides additional safety barriers that are not feasible with conventional methods.

The commercial demonstration results describe the successful deployment of the novel system, potentially yielding up to five-fold efficiency improvement compared to legacy techniques widely accepted in the industry. This new approach enables a significant advancement in wellbore intercept techniques, paving the way for enhanced operational efficiency, safety, and success in challenging wellbore environments.
Combining Machine-Learning and Physics-Based Models to Mitigate Stick-Slip in Real-Time
Authors: Yahia Hana , Romary Thomas , Gerbaud Laurent , Figluizzi Bruno , Di Meglio Florent , Menand Stephane , Mahjoub Mohamed
Published: February 2024

Downhole vibrations can lead to significant drilling problems in unconventional wells, such as frequent tool failures that increase drilling costs. Detecting these vibrations during drilling is crucial for enhancing drilling practices. One of the most destructive types of downhole vibrations is torsional stick-slip, characterized by fluctuations in bit rotation speed between zero and several times the surface rotation speed. Typically, surface data is used for real-time diagnosis of this drilling dysfunction. In recent years, Artificial Intelligence (AI)-based detection algorithms have increasingly been proposed in the literature.

However, a key drawback of AI methods is their limited applicability to wells in the same field with similar geological formations and bottom-hole assemblies (BHAs). This paper aims to address this limitation and explore solutions for generalizing these approaches. It does so by employing appropriate data normalization methods, transfer learning, and the inclusion of physics-based features. Using historical offset well data, this paper presents trained and tested machine learning models capable of predicting the stick-slip index (SSI) using sequences of surface measurements and physical features. This model can be deployed in real-time on drilling rigs to provide diagnostics and recommendations.
An Advanced Simulation Model for Drawworks and Fastline Dynamics Uncovers Risks of Spooling Errors and Other Hazards
Authors: Kyllingstad Å. , Rajic I. , Krijnen A.
Published: February 2024

The fastline is the part of the drilling line running between the drawworks drum and first sheave of the crown block assembly. Lateral vibrations of the fastline can be severe, have a negative effect on wear rates, and can cause damage to equipment with subsequential downtime. In the worst cases, severe vibrations can cause injury or even be fatal to personal. The goal of this paper is to show how a simulation model can help to identify risk factors and remedies to minimize the likelihood of spooling errors and other hazards.

This paper presents the results from an advanced simulation model describing both the generation and decay of fastline vibrations. The model includes a dynamic drawworks model having many features, such as a multilayer Lebus drum spooling, line elasticity, sheave and line inertia, and realistic speed control response of the drawworks motors. The simulation results strongly indicate that a dominating high-risk factor for error spooling is a low fastline tension force resulting from a combination of a low hook load and dynamic effects, like a high fastline speed and a rapid speed ramp-down (high deceleration rate). Other risk factors include poor damping of the generated fastline vibrations and high fastline inclination (deviation from vertical). Even though inherent bending resistance of the wire rope is a significant damping mechanism for high-frequency vibrations, it is very weak for low-frequency vibrations generated by tension variations or by axial deflection speed reversal at layer shifts. The improved model also shows that a conventional stabilizer dampens fastline vibrations poorly. In contrast, a new type of the stabilizer, which is placed closer to the fast sheave and uses passive but tuned dampeners, shows promise. Even though it is placed at a further distance from the drum, simulations strongly indicate that it can effectively dampen low frequency fastline vibrations and thereby decrease the risk of hazards.
Application of Hydraulic Port Collars in Two Stage Cementing Operations Reduces Rig Time/Drilling Cost in the Permian Basin
Authors: Giffin David , Ortez Ybes , O’Grady Tom , Loginov Arthur , Venus Greg
Published: February 2024

Operators in the Permian Basin have been performing two stage cementing operations on their casing strings for decades utilizing conventional diverter tool technology, often in combination with casing annulus packers.

Over time, issues with legacy diverter tools (DV) have been identified and solutions sought. These issues range from longer than desired time to drill-out the DV tool, reluctance to drill-out a DV tool with a directional assembly due to drill bit dulling and premature drilling motor/MWD failures, damage to the DV tool while drilling causing leaks and remediation, and an inability to pressure test the whole casing string after cementing. A development effort was made to eliminate these issues. The Hydraulic Port Collar (HPC) was designed and extensive qualification/testing of the HPC design was performed prior to field deployment. Running procedures were written and revised in consultation with a variety of operators. Several wells were identified for field trials. The wells were selected based on the operator’s desire to eliminate a DV tool drill-out. The wells had complex directional plans that required high bend drilling motors resulting in the operator’s reluctance to drill-out conventional DV tools with the curve BHA’s.

The hydraulic port collar functioned as designed on all field trials. Pressure readings from the cement trucks confirmed the tools opened within the calculated pressures and closed and sheared out within the calculated pressures. Full communication of compressed volume, from the float collar to surface was achieved, allowing the operator to perform a full string casing test. The wiper plug was mechanically confirmed as released from the HPC and subsequently pushed to bottom and drilled up when the shoe track was drilled out. Utilizing curve BHA’s with 2.12° to 2.38° bend motors, all wells were drilled and landed in the drilling window with one curve BHA run. As a result, dedicated DV tool drill-out runs were eliminated, no unusual damage or dulling of the curve BHA was observed and no post drill-out damage/leaks at the HPC were experienced. A review of the field trials showed efficiency gains up to 40% when compared to previous operations where legacy DV tools had been deployed. These trials confirm that the novel Hydraulic Port Collar can increase operator efficiency in wells that require two stage cementing operations.

This paper will document case histories and lessons learn to date.
Prioritization of maternal and newborn health policies and their implementation in the eastern conflict affected areas of the Democratic Republic of Congo: a political economy analysis.
Authors: Bigirinama Rosine Nshobole , Mothupi Mamothena Carol , Mwene-Batu Pacifique Lyabayungu , Kozuki Naoko , Chiribagula Christian Zalinga , Chimanuka Christine Murhim'Alika , Ngaboyeka Gaylord Amani , Bisimwa Ghislain Balaluka
Published: February 2024

Background: Maternal and neonatal mortality remains a major concern in the Democratic Republic of Congo (DRC), and the country's protracted crisis context exacerbates the problem. This political economy analysis examines the Maternal and Newborn Health (MNH) prioritization in the DRC, focusing specifically on the conflict-affected regions of North and South Kivu. The aim is to understand the factors that facilitate or hinder the prioritization of MNH policy development and implementation by the Congolese government and other key actors at national level and in the provinces of North and South Kivu.
Methods: Using a health policy triangle framework, data collection consisted of in-depth interviews with key actors at different levels of the health system, combined with a desk review. Qualitative data was analysis using inductive and then deductive approaches, exploring the content, process, actor dynamics, contextual factors and gender related factors influencing MNH policy development and implementation.
Results: The study highlighted the challenges of prioritizing policies in the face of competing health and security emergencies, limited resources and governance issues. The Universal Health Coverage policy seems to offer hope for improving access to MNH services. Results also revealed the importance of international partnerships and global financial mechanisms in the development of MNH strategies. They highlight huge gender disparities in the MNH sector at all levels, and the need to consider cultural factors that can positively or negatively impact the success of MNH policies in crisis zones.
Conclusion: MNH is a high priority in DRC, yet implementation faces hurdles due to financial constraints, political influences, conflicts, and gender disparities. Addressing these challenges requires tailored community-based strategies, political engagement, support for health personnel, and empowerment of women in crisis areas for better MNH outcomes.
Drug-resistant bacteria were found to contaminate inanimate surfaces and equipment in the Intensive Care Unit at Kawempe National Referral Hospital.
Authors: Aston Aine , Nalwanga Winnie , Magulye Maximilian A.K. , Edrisa Ssemwanga , Sande Obondo James , Katagirya Eric
Published: February 2024

Background
Hospital inanimate surfaces and equipment in intensive care units (ICUs) provide a worrisome reservoir for drug-resistant microorganisms, which cause healthcare-associated infections (HCAIs) in mostly developing countries. This study aimed to determine the prevalence and antimicrobial susceptibility profiles of bacteria isolated from inanimate surfaces in the intensive care unit at Kawempe National Referral Hospital (KNRH).
Methods
A cross-sectional study was conducted from December 2022 to April 2023 in the ICU at KNRH. Random sampling was used to swab 15 pieces of selected equipment on points of contact with the user and points of contact with the patient and inanimate surfaces. The samples were analyzed for bacterial growth using standard microbiological methods. The antimicrobial susceptibility of the identified bacterial isolates was tested against commonly used antibiotics. All the data were analyzed in STATA version 12.
Results
A total of 76.2% (76/101) of the samples were positive for bacterial growth. The most common bacterial contaminants of inanimate surfaces and equipment in the adult ICU and neonatal ICU were CNSs (46.9% vs. 34.64%). All the gram-negative bacteria isolated were resistant to ceftazidime and ampicillin. Among the Enterobacterales strains tested for ESBL production, 62.5% were ESBL positive
Conclusion
The intensivecare unit (ICU) environment is known to act as areservoir of potentially pathogenic microorganisms. Inanimate surfaces and medical equipment were found to be highly contaminated,and the predominant bacteria isolated from inanimate surfaces and medical equipment were coagulase-negative staphylococci, Acinetobacter species, Bacillus species, Micrococcus species, A. baumannii and K. pneumoniae. These isolates can potentially cause health care-associated infections. Therefore, routine surveillance of hospital inanimate surfaces and medical equipment is needed for timely intervention to reduce environmental contamination by resistant bacterial species and prevent hospital infection.
Efficient value encoding through convergence of tactile and visual value information in the primate putamen
Authors: Kim Hyoung , Hwang Seong-Hwan , Park Doyoung , Lee Ji-Woo , Lee Sue-Hyun
Published: February 2024

Primates use fingers and eyes to discriminate diverse values from tactile and visual stimuli for decision-making. However, the limited number of neurons raises the question of how the brain processes diverse values with this constraint. Here, we discovered that tactile and visual values converge to form an abstract representation of value in single putamen neurons, enabling efficient value-coding with fewer neurons. Humans and monkeys performed tactile and visual value discrimination tasks while neural responses were examined. The human putamen selectively represented both values in fMRI. Single-unit electrophysiology in the macaque putamen further revealed that half of value-processing neurons encoded both values, regardless of sensory inputs, showing value abstraction in single neurons. Notably, incorporating more of these bimodal value neurons enables discriminating values with a smaller number of total neurons. Our data indicate that the basal ganglia system abstracts different sensory values within individual neurons, facilitating efficient decision-making despite limited resources.
Analysis of the Epidemiological and Surgical Predictors of Frozen shoulder Observed in a 5-year Pilot at Zhejiang Provincial Hospital of Chinese Medicine
Authors: Qiao Zukang , Pang Xi , Jiang Nengyi , Xiang Li , Li QiuShuang , Xiong Junlong
Published: February 2024

Background
Frozen shoulder constitutes a disease category associated with significant clinical morbidity and complications. However, the precise risk factors contributing to its development remaining unidentified.
In this study, a clinical database was established through the collection of medical records from frozen shoulder patients who were hospitalized in the Department of Tuina at The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine) between 1 January 2017 and 30 December 2022. A randomized case-control design was employed to identify potential risk factors by analyzing the demographic characteristics of the patients. Additionally, logistic regression analysis was conducted to ascertain the prognostic risks associated with frozen shoulder, including factors such as age, gender, and surgical interventions.
Methods
A total of 176 patients with frozen shoulder with a median age of 55.94 years were enrolled in this study. Complicated diabetes (B, 2.517; OR, 12.396; 95% CI, 3.656-42. 028; P=.000), and cervical spondylosis (B, 1.495; OR, 4.459; 95% CI, 1.857-10.709; P=.001) were at higher risk in patients with bursitis compared to controls. In the intention to treat analysis (ITT) population, 125 persons choose surgical treatment and 51 choose conservative treatment, and long duration of illness (B, -0.716; OR, 0.489; 95% CI, 0.260-0.916; P=.026) and long hospital stay (B, 0.46; OR, 1.582; 95% CI, 1.008-2.482; P=.046), accompanied by cervical spondylosis (B, 1.149; OR, 3.155; 95% CI, 1. 335-7.453; P=.009) and hypertension (B, 1.279; OR, 3.593; 95% CI, 1.508-8.556; P=.004) patients were more likely to opt for surgery, and health insurance had little impact on whether patients operated or not (P>0.05).
Results
The study identified various risk factors for frozen shoulder, including obesity, thyroid nodules, diabetes, and cervical spondylosis. Additionally, patients with long-term disease, short hospital stays, and concomitant hypertension or cervical spondylosis demonstrated a higher likelihood of choosing surgical intervention.
Biological characteristics and metabolic phenotypes of different anastomosis groups of Rhizoctonia solani strains
Authors: Sun Meili , Wang Hancheng , Zhang Songbai , Li Zhen , Ye Guo
Published: February 2024

Background
Rhizoctonia solani is an important plant pathogen worldwide, and causes serious target spot disease in tobacco in the last five years. This research studied the biological characteristics of four different anastomosis groups (R. solani AG-3, R. solani AG-5, R. solani AG-6, R. solani AG-1-IB) of R. solani from tobacco, and analyzed the metabolic phenotype differences of these strains using metabolic phenotype technology.
Results
The results showed that the suitable temperature for mycelial growth of four anastomosis group strains were all from 20 to 30 oC, and for sclerotia formation were from 20 to 25 oC. Under different lighting conditions, R. solani AG-6 strains produced the most sclerotium, followed by R. solani AG-3, R. solani AG-5 and R. solani AG-1-IB. All strains had strong oligotrophic survivability, and can grow on water agar medium without any nitrutions. They exhibited three types of sclerotia distribution form, including dispersed type (R. solani AG-5 and R. solani AG-6), peripheral type (R. solani AG-1-IB), and central type (R. solani AG-3). They all presented different pathogenicities in tobacco leaves, with the most virulent was noted by R. solani AG-6, followed by R. solani AG-5 and AG-1-IB, finally was R. solani AG-3. R. solani AG-1-IB strains firstly present symbtom about inoculation. Metabolic fingerprints of four anastomosis groups were different to each other. R. solani AG-3, AG-6, AG-5 and AG-1-IB strains efficiently metabolized 88, 94, 71 and 92 carbon substrates, respectively. Nitrogen substrates of amino acids and peptides were the significant utilization patterns for R. solani AG-3. R. solani AG-3 and AG-6 showed a large range of adaptabilities and were still able to metabolize substrates in the presence of the osmolytes, including up to 8% sodium lactate. Four anastomosis groups all showed active metabolism in environments with pH values from 4 to 6 and exhibited decarboxylase activities.
Conclusions
The biological characteristics of different anastomosis group strains varies, and there are differences in the metabolic phenotype characteristics of different anastomosis group strains towards carbon source, nitrogen source, pH, and osmotic pressure.
Exploring the Co-occurrence and Latent Class Analysis of Adverse Childhood Experiences in University Students in Lahore, Pakistan
Authors: Fatima Rabia , Saleem Javeria , Ishaq Muhammad , Ali Zulfiqar , Irshad Fatima , Fatima Aneela , Bukhari Gul Mehar Javaid , Khan Sohail Mahmood , Abdi Gholamreza
Published: February 2024

Adverse childhood experiences (ACEs) are one of the major public health concerns and act as a predisposing factor leading to numerous chronic health issues. This study aims to determine the prevalence and likelihood of the co-occurrence of different childhood adversities and explore the latent classes in university students in Lahore, Pakistan. An online version of the ACE-IQ was used to collect data from students of randomly selected universities in Lahore with their consent. Descriptive statistics, the chi-square test, Cramer-V, and latent class analysis (LCA) were applied to the collected dataset. All domains had a prevalence of between 30 and 85%, with community/peer violence exposure being the most common (82.9%), followed by physical abuse exposure (65.2%). According to the LCA results, three classes were observed, i.e., Class 1, High/Multiple ACEs; Class 2, Low ACEs; and Class 3, Neglect, Physical Abuse and Violence related ACEs. The percentages of our population in Classes 1, 2, and 3 were 21.38%, 39.26%, and 39.36%, respectively. This study concluded that the prevalence of ACEs is very high in university students in Lahore, with a moderately strong correlation among different adversities, which increases the likelihood of their co-occurrence.
EPA and DHA inhibit LDL-induced upregulation of human adipose tissue NLRP3 inflammasome/IL-1β pathway and its association with diabetes risk factors
Authors: Lamantia Valérie , Bissonnette Simon , Beaudry Myriam , Cyr Yannick , Des Rosiers Christine , Baass Alexis , Faraj May
Published: February 2024

Elevated numbers of atherogenic lipoproteins (apoB), mostly circulating as low-density lipoproteins (LDL), predict diabetes risk. We recently reported that native LDL upregulate the NLRP3 inflammasome/interleukin-1β (IL-1β) pathway in human white adipose tissue (WAT); however, nutritional approaches to target this remain unknown. We tested the hypotheses that eicosapentaenoic (EPA) and docosahexaenoic (DHA) acids treat LDL-induced upregulation of the WAT NLRP3 inflammasome/ IL-1β-pathway and its relation to T2D risk factors in vivo and ex vivo. Forty subjects without chronic disease were enrolled into a 12-week-intervention with EPA and DHA (2.7 g/d from Webber Naturals), of whom 17 subjects with high-apoB and 16 with low-apoB completed the intervention. Supplementation with EPA and DHA abolished baseline group-differences in WAT IL-1β-secretion between subjects with high- and low-apoB. Contrary to baseline, native LDL failed to stimulate WAT IL-1β-secretion after the omega-3 intervention and rather inhibited IL-1β-secretion induced by microbial LPS. EPA and DHA also improved β-cell function and postprandial fat metabolism, in relation with their circulating levels, and blunted the association of WAT NLRP3 and IL1B mRNA expression and IL-1β-secretion with the risk factors for T2D. In line ex vivo, treatment of WAT with EPA and DHA inhibited IL-1β-secretion in a dose-dependent manner. In conclusion, supplementation with EPA and DHA treats LDL-induced upregulation of the NLRP3 inflammasome/IL-1β pathway and related metabolic anomalies, which may aid the prevention of CVD and T2D in subjects with elevated plasma apoB. ClinicalTrials.gov Identifier: NCT04496154
Vitamin D-Related risk factors for preterm and full-term infants at birth: A retrospective study in Wuxi, China
Authors: Xiao Xiao , Wu Man , Zou Lian , Jin Xin , Zhang Yun , Zheng Xiaomin
Published: February 2024

Background/Objectives:
Vitamin D is thought to play a role in early immune development of infants. However, national data on vitamin D status in newborns is limited in China. We aimed to evaluate the vitamin D status in preterm and full-term neonates and its influencing factors in Wuxi, southeastern China.
Subjects/Methods:
813 infants born were recruited in this study from May 2020 to May 2022, including 167 very preterm (< 32+ 0 weeks), 454 preterm (32+ 0-36+ 6 weeks) and 192 full-term (≥ 37+ 0 weeks) newborns. The umbilical cord serum level of 25-hydroxyvitamin D (25(OH)D) was measured.
Results
The median level of serum 25(OH)D was 35.9 nmol/L, and 82.7% of them were vitamin D deficient. The serum 25(OH)D level was lower in full-term infants compared with preterm and very preterm infants at birth, while there was no significant difference (preterm, 95% confidence interval [CI], 0.484, 1.657, p = 0.725; very preterm, 95% CI, 0.434, 2.061, p = 0.946) in the prevalence of vitamin D deficiency among them. It was found that vitamin D deficiency in newborns was significantly associated with season of birth (Spring, 95% CI, 0.128,0.541, p < 0.001; Summer, 95% CI, 0.101, 0.491, p < 0.001; Autumn, 95% CI, 0.106, 0.465, p < 0.001) and maternal pre-pregnancy BMI (< 25 kg/m2, 95% CI, 0.150, 0.514, p < 0.001; 25–30 kg/m2, 95% CI, 0.277, 0.916, p = 0.025) after controlling for maternal age, birth weight and gestational age. Conclusions: More attentions should be focused on the nutritional vitamin D status of infants born in winter. Infants born to women who are obese before pregnancy are likely to have greater odds of vitamin D deficiency at birth which requires urgent attentions. Adequate daily vitamin D supplementation for newborns is recommended and warranted immediately after birth.
miR-183-5p attenuates the effect of sorafenib on human hepatocellular carcinoma via inhibiting SOCS6/JAK2/STAT3 pathway
Authors: Chen Che , Zhao Yanyu , Song Yanmei , Liu Qianqian , Sun Xinglu , Liu Fang , Chu Huiyuan , Lu Yan , Bao Shisan
Published: February 2024

Objective:
MicroRNA plays a crucial role in the progression of hepatocellular carcinoma (HCC) and the resistance of HCC cells to sorafenib (SOR). Elevation of miR-183-5p is associated with poor survival among patients with HCC. This study aimed to investigate the impact of miR-183-5p on SOR resistance in HCC as well as its related signaling pathway. The objective is to provide new insights, directions, and a theoretical basis for the clinical diagnosis and treatment of HCC.
Design:
Human normal hepatocytes (LO2) and HCC cell lines (HepG2, Huh7, and MHCC97H) were cultured, and were constructed with miR-183-5p inhibition and SOCS6 overexpression. Biotrust analysis and qRT-PCR were employed to assess the expression of miR-183-5p in liver cancer tissues or cells, respectively. Flow cytometry determined apoptosis rate in each group of cells, while CCK was used for detecting the 50% inhibitory concentration (IC50) of HCC followed SOR treatment. Western blotting was used to detect protein expression changes of SOCS6, p-JAK2, JAK2, p-STAT3, and STAT3.
Results:
Bioinformatics revealed significantly high expression of miR-183-5p in liver cancer compared to normal tissues. Consistent with this analysis, the expression of miR-183-5p was upregulated in human HCC cell lines, in order of Huh7, HepG2, and MHCC97H, compared to that of non-HCC cells. CCK-8 assays results shown that the IC50 value of sorafenib in Huh7 cells with higher expression levels of miR-183-5p were more high than Hep3B and MHCC97H cells with the relative lower expression levels of miR-183-5p. SOCS6 was elevated with the miR-183-5p inhibition compared to the control. Furthermore, the IC50 value of sorafenib was significantly decreased following miR-183-5p inhibition and increased in the miR-183-5p overexpression compared to the mock treatment. Conversely, the IC50 value of sorafenib in the SOCS6 overexpression group was significantly decreased compared to the control.
Conclusions:
Dysregulation of the miR-183-5p-SOCS6/JAK2/STAT3 axis plays a critical role in patients' responses to SOR treatment. Manipulation of this axis could potentially enhance the survival of patients with HCC, especially in the context of addressing drug resistance.
Phycoremediation of As(III) and Cr(VI) by Desmodesmus subspicatus: Impact on growth and biomolecules (carbohydrate, protein, chlorophyll and lipid) – A dual mode investigation
Authors: Ganguly Anisha , Nag Soma , Bhowmick Tridib Kumar , Gayen Kalyan
Published: February 2024

Microalgae are under research focus for the simultaneous production of biomolecules (e.g., biofuels) and bioremediation of toxic materials from wastewater. The current study explores the capability of indigenously isolated microalgae (Desmodesmus subspicatus) for phycoremediation As(III) and Cr(VI) along with the production of biomolecules by alternating its extracellular and intracellular compositions.Desmodesmus subspicatussurvived up to the toxicity level of 10 mg/L for As(III) and 0.8 mg//L for Cr(VI). A decline in carbohydrate accumulation (⁓70%) at 10 mg/L of As(III) concentration was obtained. An increased content of protein (⁓28%) and lipid (by ⁓32%) within the cells ofDesmodesmus subspicatuswas observed when grown in 0.5 and 0.2 mg/L As(III) concentrations respectively. A descending trend in carbohydrate accumulation was noted with increasing Cr(VI) concentration and the least (~44%) was recorded at 0.8 mg/L Cr(VI).Desmodesmus subspicatusshowed an excellent maximum removal efficiency for Cr(VI) and As(III) as 77% and 90% respectively.
Temporal Variations of Rainfall and Temperature in Northwestern Bangladesh Using Mann-Kendall Trend Test
Authors: Prodhan Md Mehedi Hasan , Islam Md. Bashirul , Rahman Sheikh Mokhlesur
Published: February 2024

This study utilized the Mann-Kendall (MK) test and Sen’s slope (SS) to investigate the trend in annual and monthly rainfall and maximum (Tmax) and minimum temperature (Tmin) in the northwestern region of Bangladesh, encompassing six meteorological station data spanning the years 1982 to 2022, except for Sayedpur from 1991 to 2022. A serial correlation test was conducted on all the time series to assess the sequential interdependence among the data. A modified version of the MMKY test was applied for serially correlated data. For annual rainfall, a decreasing trend was observed at every station, but the result was significant (p < 0.01) only at the Rangpur and Dinajpur stations. An increasing trend in Tmax and Tmin was observed at every station; however, Tmin at Sayedpur station and Tmax at Bogra and Ishurdi stations showed insignificant (p > 0.05) trends. The rainfall decrease in Rangpur station (14.12 mm/year) was larger than in other stations. Tmin increased by 0.028, 0.024, 0.04, 0.025, 0.028, and 0.011 °C/year at Bogra, Rajshahi, Rangpur, Dinajpur, Ishurdi, and Sayedpur stations, respectively. Similarly, Tmax increased by 0.013, 0.02, 0.015, 0.021, 0.005, and 0.048 °C/year at Bogra, Rajshahi, Rangpur, Dinajpur, Ishurdi, and Sayedpur stations, respectively. Finally, the Rainfall Anomaly Index (RAI) was utilized to illustrate the temporal fluctuations in annual precipitation. The reduced rainfall and increasing temperatures accelerate water stress and hinder crop growth and yield. Therefore, the implementation of adaptation measures is necessary to ensure sustainable agricultural output in northwestern Bangladesh.
Machine-Learning Enhanced Prediction of Need for Hemorrhage Resuscitation after Trauma – The ShockMatrix Pilot Study
Authors: GAUSS TOBIAS , MOYER JEAN-DENIS , COLAS CLELIA , PICHON MANUEL , DELHAYE NATHALIE , WERNER MARIE , RAMONDA VERONIQUE , SEMPE THEOPHILE , MEDJKOUNE SOFIANE , JOSSE JULIE , JAMES ARTHUR , HARROIS ANATOLE , Group The Traumabase
Published: February 2024

Importance:
Decision-making in trauma patients remains challenging and often result in deviation from guidelines. Machine-Learning (ML) enhanced decision-support could improve hemorrhage resuscitation.
Aim
To develop a ML enhanced decision support tool to predict Need for Hemorrhage Resuscitation (NHR) (part I) and test the collection of the predictor variables in real time in a smartphone app (part II).
Design, Setting, and Participants:
Development of a ML model from a registry to predict NHR relying exclusively on prehospital predictors. Several models and imputation techniques were tested. Assess the feasibility to collect the predictors of the model in a customized smartphone app during prealert and generate a prediction in four level-1 trauma centers to compare the predictions to the gestalt of the trauma leader.
Main Outcomes and Measures:
Part 1: Model output was NHR defined by 1) at least one RBC transfusion in resuscitation, 2) transfusion ≥ 4 RBC within 6 hours, 3) any hemorrhage control procedure within 6 hours or 4) death from hemorrhage within 24 hours. The performance metric was the F4-score and compared to reference scores (RED FLAG, ABC). In part 2, the model and clinician prediction were compared with Likelihood Ratios (LR).
Results
From 36325 eligible patients in the registry (Nov 2010 - May 2022), 28614 were included in the model development (Part 1). Median age was 36 [25–52], median ISS 13 [5–22], 3249/28614 (11%) corresponded to the definition of NHR. A XGBoost model with nine prehospital variables generated the best predictive performance for NHR according to the F4-score with a score of 0.76 [0.73–0.78]. Over a 3-month period (Aug - Oct 2022), 139 of 391 eligible patients were included in part II (38.5%), 22/139 with NHR. Clinician satisfaction was high, no workflow disruption observed and LRs comparable between the model and the clinicians.
Conclusions and Relevance:
The ShockMatrix pilot study developed a simple ML-enhanced NHR prediction tool demonstrating a comparable performance to clinical reference scores and clinicians. Collecting the predictor variables in real-time on prealert was feasible and caused no workflow disruption.
Comparative study of COVID-19 infection in renal transplant recipients and non transplant recipients
Authors: Pan Jianyong , lan Xiangyu , Peng Yuanzheng , Chen Weijun , Zheng Yitao , Liu Yongdong , Fu Yingxin
Published: February 2024

To analyse the difference in COVID-19 infection between kidney transplant patients and non-transplant patients. We included post-transplant patients with COVID-19 infection who attended Shenzhen No. 3 Hospital from December 2022 to February 2023, and enrolled the general population with COVID-19 infection who were hospitalized during the same period, matched by age and gender. They were divided into Kidney Transplant Recipients group (KTR) (n=194) and Non-Kidney Transplant Recipients Group（NKTR）(n=516) and the basic information, clinical symptoms, laboratory data, treatments and outcomes of these two groups were compared. The proportion of the renal transplant population classified as severe and critical was 15.5%, which was significantly higher than that in NKTR group (P < 0.05); the proportion of patients with pneumonia was also significantly higher than that in NKTR group. The mean maximum fever temperature was slightly higher in the NKTR(P<0.001);Kidney transplant population having lower absolute lymphocyte counts on admission and 7 days after admission than the general population, with statistically significant differences（P<0.001, P＜0.001). The use of intravenous hormones was significantly higher (42.8% vs. 6.0%, p=0.000), as was the use of small molecules such as Azvudine and Paxlovid, compared to the general population. A total of 10 patients in the included population required ICU admission, all in the KTR group; six patients experienced death, also in the renal transplant group. Conclusion: Post-transplant COVID-19 infections are more severe and require hormonal and small molecule antiviral therapy, and the prognosis is worse than in the general population.
Trial registration
This study was approved and supervised by the ethics committee of the Third People's Hospital of Shenzhen (approval number 2023-036-02) and firstly registered in 03/07/2023, registration number was NCT05926076.