bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Utility of Maternal TORCH Screening Due to Obstetrical Indications in Detecting Congenital Infections: A Retrospective Observational Study
Authors: Abu Shqara Raneen , Or Shany , Abu Zraki Abdallah , Rizik Jeries , Glikman Daniel , Rechnitzer Hagai , Lowenstein Lior , Frank Wolf Maya 
Published: September 2023

Background:
The diagnostic yield of TORCH screening for obstetrical indications is unclear. We evaluated TORCH testing results among women with intrauterine growth restriction (IUGR), polyhydramnios and oligohydramnios; and associations with congenital infections in neonates.

Method:
This retrospective single-center study included all the women diagnosed with IUGR, polyhydramnios or oligohydramnios who underwent serological TORCH testing during 2010–2019. TORCH screening included Toxoplasma, cytomegalovirus (CMV), rubella IgM and IgG. The data, which were cross-referenced with data of neonates with congenital TORCH infections during the same period, included indications for neonatal testing, sonographic findings and neonatal ophthalmologic and hearing findings.

Result:
Six women of 771 (0.8%) were diagnosed with primary TORCH infection: 4 (0.5%) with toxoplasmosis, and 2 (0.3%) with CMV. None had a confirmed congenital infection. The rates of positive maternal TORCH screening in IUGR and polyhydramnios were 2.1% and 0.6%, respectively. Maternal TORCH infection was not identified in any woman with oligohydramnios or severe polyhydramnios. None of the neonates with congenital infection were screened for TORCH during pregnancy due to polyhydramnios, oligohydramnios or IUGR. Among the neonates with congenital CMV, the most common indication for performing neonatal CMV polymerase chain reaction was suspected primary maternal infection during pregnancy due to symptomatic CMV. No incidences of congenital rubella were noted in the last decade in our medical center.

Conclusion:
Our results suggest that routine TORCH screening in pregnancies complicated with IUGR, polyhydramnios or oligohydramnios should be avoided. Suggestive maternal symptoms and specific fetal sonographic features should prompt testing for CMV and Toxoplasma infection.
Use of IDEAL-IQ in Quantifying Femoral Bone Marrow Involvement in Gaucher Disease
Authors: Hou Bo , Cidanwangjiu  , Zhang Haiping , Wang Fengdan , Qiu Zhengqing , Zhang Yan , Jin Zhengyu 
Published: September 2023

Objective
To quantitatively measure femoral bone marrow involvement in patients with Gaucher disease (GD) by using fat fraction (FF) derived from the iterative decomposition of water and fat with echo asymmetry and least-squares estimation quantitation (IDEAL-IQ) technique.

Methods
Bilateral femora of 23 patients with type 1 GD receiving low-dose imiglucerase treatment were prospectively scanned using structural magnetic resonance imaging sequences and an IDEAL-IQ sequence. Femoral bone marrow involvement was evaluated by both semiquantification (bone marrow burden [BMB] score based on magnetic resonance imaging structural images) and quantification (FF derived from IDEAL-IQ) methods. These patients were further divided into subgroups according to whether they underwent splenectomy or had bone complications. The interreader agreement of measurements and the correlation between FF and clinical status were statistically analyzed.

Results
In patients with GD, both BMB and FF evaluation of femora showed good interreader concordance (intraclass correlation coefficient = 0.98 and 0.99, respectively), and FF highly correlated with BMB score (P < 0.001). The longer the duration of disease, the lower the FF (P = 0.026). Femoral FF was lower in subgroups with splenectomy or bone complications than those without splenectomy or bone complications (0.47 ± 0.08 vs 0.60 ± 0.15, 0.51 ± 0.10 vs 0.61 ± 0.17, respectively, both P < 0.05).

Conclusion
Femoral FF derived from IDEAL-IQ could be used to quantify femoral bone marrow involvement in patients with GD, and low bone marrow FF may predict worse outcomes of GD patients in this small-scale study.
Muscle Reference Values From Thoracic and Abdominal CT for Sarcopenia Assessment
Authors: Tonnesen P. Erik , Mercaldo Nathaniel D. , Tahir Ismail , Dietrich Anna-Sophia W. , Amayri Wael , Graur Alexander , Allaire Brett , Bouxsein Mary L. , Samelson Elizabeth J. , Kiel Douglas P. , Fintelmann Florian J. 
Published: September 2023

Background
Loss of muscle mass is a known feature of sarcopenia and predicts poor clinical outcomes. Although muscle metrics can be derived from routine computed tomography (CT) images, sex-specific reference values at multiple vertebral levels over a wide age range are lacking.

Objective
The aim of this study was to provide reference values for skeletal muscle mass and attenuation on thoracic and abdominal CT scans in the community-based Framingham Heart Study cohort to aid in the identification of sarcopenia.

Materials and Methods
This secondary analysis of a prospective trial describes muscle metrics by age and sex for participants from the Framingham Heart Study without prior history of cancer who underwent at least 1 CT scan between 2002 and 2011. Using 2 previously validated machine learning algorithms followed by human quality assurance, skeletal muscle was analyzed on a single axial CT image per level at the 5th, 8th, 10th thoracic, and 3rd lumbar vertebral body (T5, T8, T10, L3). Cross-sectional muscle area (cm2), mean skeletal muscle radioattenuation (SMRA, in Hounsfield units), skeletal muscle index (SMI, in cm2/m2), and skeletal muscle gauge (SMRA·SMI) were calculated. Measurements were summarized by age group (<45, 45–54, 55–64, 65–74, ≥75 years), sex, and vertebral level. Models enabling the calculation of age-, sex-, and vertebral-level–specific reference values were created and embedded into an open access online Web application.

Results
The cohort consisted of 3804 participants (1917 [50.4%] males; mean age, 55.6 ± 11.8 years; range, 33–92 years) and 7162 CT scans. Muscle metrics qualitatively decreased with increasing age and female sex.

Conclusions
This study established age- and sex-specific reference values for CT-based muscle metrics at thoracic and lumbar vertebral levels. These values may be used in future research investigating the role of muscle mass and attenuation in health and disease, and to identify sarcopenia.
Impact of Coronavirus Disease 2019 on Clinical Outcomes of Robotic Cholecystectomy
Authors: Kudsi Omar Yusef , Kaoukabani Georges , Friedman Alexander , Bou-Ayash Naseem , Bahadir Jenna , Gokcal Fahri 
Published: September 2023

Background:
The coronavirus disease 2019 (COVID-19) pandemic strained the health care sector, putting severe constraints on surgical departments. In this study, we evaluate the impact of the pandemic on the outcomes of patients undergoing robotic cholecystectomy (RC).

Patients and Methods:
Patients who underwent RC 1 year before and after March 2020 were included in this retrospective study and assigned accordingly to the pre or post-COVID group. Pre, intra, and postoperative variables were compared between groups.

Results:
In total, 110 patients were assigned to the pre-COVID group versus 80 in the post-COVID group. There were no differences in the demographics, except for a higher rate of previous gallbladder disease in the pre-COVID group (35.5% vs 13.8,% P < 0.001). The post-COVID group had a higher rate of emergent RCs (62.5% vs 39.1%, P = 0.002). Operative times were greater in the post-COVID group due to the more frequent participation of clinical fellows in the cases. The median hospital length of stay for both groups was 1 day, with higher rates of same-day discharge (pre-COVID 40.9% vs post-COVID 57.5%, P = 0.028). Complications were comparable between both groups, with no recorded cases of COVID-19 contraction within the virus incubation period. The median follow-up was 10 months for the entire cohort.

Conclusion:
During the COVID-19 pandemic, an increase in emergent cases, as well as higher rates of same-day discharge, were recorded, with no impact on postoperative outcomes in patients undergoing RC.
Early Bowel Obstruction after Bariatric Surgery: An Analysis of the 2020-2021 MBSAQIP Database
Authors: Clapp Benjamin , Abi Mosleh Kamal , Corbett John , Salame Marita , Hage Karl , Kurian Marina , Zundel Natan , Ghanem Omar M. 
Published: September 2023

Background:
The Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program evaluates 30-day outcomes of bariatric cases performed in the United States. The Participant Use File in 2020 introduced bowel obstruction (BO). We compared the rates of BO, risk factors, and postoperative outcomes after laparoscopic Roux-en-Y gastric bypass (RYGB), sleeve gastrectomy (SG), and duodenal switch (DS).

Methods:
Retrospective analysis of patients who underwent laparoscopic RYGB, SG, or DS obtained from the 2020-2021 Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program. Patients who underwent either as a primary procedure with a body mass index >35 kg/m2 were selected. Baseline characteristics, operative details, and postoperative complications were collected. The outcome of interest was BO occurring within 30 days.

Results:
A total of 205,533 cases of which 148,944 were SG (72.4%), 54,606 were RYGB (26.5%), and 1983 were DS (1%). BO occurred in 0.74%, 0.4%, and 0.03% of patients who underwent an RYGB, DS, or SG, respectively. Patients with a BO in the RYGB group were more likely to be on immunosuppressive therapy (5.4% vs. 1.9%, P<0.001) with longer operative time (136.2 min±58.0 min vs. 117.4 min±53.6 min, P<0.001). SG patients with a BO were older (47.5±13.6 vs. 41.9±11.6, P=0.011) with longer operating times (98.6±63.8 vs. 68.9±33.4, P=0.002). Patients in the RYGB group with a BO had the highest rates of readmissions (71.9%) and reoperations (58.4%).

Conclusions:
Early bowel obstruction is rare after bariatric surgery. It is more common after RYGB and least common after SG. Readmission and reoperation rates were highest in patients with BO in the RYGB group.
Endoscopic Ultrasound (EUS)-guided Drainage of Caudate Lobe Abscess: A Single Center Experience
Authors: Shah Jimil , Jena Anuraag , Singh Anupam K. , Jearth Vaneet , Dutta Usha 
Published: September 2023

Background:
Liver abscess is usually treated with medical therapy. Few patients require drainage of the collection due to large size, certain high-risk location or rupture of the collection. Percutaneous drainage is most commonly used modality for the drainage of such collection. However, caudate lobe poses a unique difficulty in percutaneous drainage due to its deep location.

Methods:
We did a retrospective analysis of all patients with caudate lobe abscess who underwent endoscopic ultrasound (EUS)-guided drainage at our center. We reviewed their indications, technical and clinical success rates of the procedure from 2020 to 2023. We also performed systemic review of published literature till June 12, 2023 showing use of EUS-guided drainage of caudate lobe abscess.

Results:
Total of 8 patients (age: 37.33 ± 12.8 y; Males 62.5%) underwent EUS-guided drainage of caudate lobe collection at our center. Six patients underwent drainage using plastic stents, 1 patient underwent using metal stent, and 1 patient had aspiration of the abscess. Technical success was achieved in all patients. One patient succumbed to background illness and clinical success could be achieved in rest of the patients. In systemic review of literature on EUS-guided drainage of caudate lobe, a total of 10 studies (17 patients) were included. All patients achieved technical success. Majority studies reported use of plastic stents or naso-cystic drains whereas only 1 case reported use of metal stents. One procedure related complication (localized para-esophageal abscess) was reported requiring endoscopic intervention for management.

Conclusion:
EUS-guided drainage of caudate lobe abscess is safe and effective. It should be used as a first-line intervention after a failed medical management.
Grid Cell Firing Patterns Maintain their Hexagonal Firing Patterns on a Circular Track
Authors: Yim Man Yi , Walton Steven , Hedrick Kathryn 
Published: September 2023

ABSTRACTIn an open two-dimensional environment, grid cells in the medial entorhinal cortex are known to be active in multiple locations, displaying a striking periodic hexagonal firing pattern covering the entire space. Both modeling and experimental data suggest that such periodic spatial representations may emerge from a continuous attractor network. According to this theory, grid cell activity in any stable 1D environment is a slice through an underlying 2D hexagonal pattern, which is supported by some experimental studies but challenged by others. Grid cells are believed to play a fundamental role in path integration, and so understanding their behavior in various environments is crucial for understanding the flow of information through the entorhinal-hippocampal system. To this end, we analyzed the activity of grid cells when rats traversed a circular track. A previous study involving this data set analyzed individual grid cell activity patterns separately, but we found that individual grid cells do not provide sufficient data for determining the under-lying spatial activity pattern. To circumvent this, we compute the population autocorrelation, which pools together population responses from all grid cells within the same module. This novel approach recovers the underlying six-peak hexagonal pattern that was not observable in the individual autocorrelations. We also use the population autocorrelation to infer the spacing and orientation of the population lattice, revealing how the lattice differs across environments. Furthermore, the population autocorrelation of the linearized track reveals that at the level of the population, grid cells have an allocentric code for space. These results are strong support for the attractor network theory for grid cells, and our novel approach can be used to analyze grid cell activity in any undersampled environment.
Uncovering Invariant Representations in Functional Neuroimaging with Deep Metric Learning
Authors: Mittal Arunesh , Sun Xiaoxiao , Paisley John , Sajda Paul 
Published: September 2023

AbstractWith the increasing ability to record neuroimaging with higher spatial and temporal resolution, there is a growing need for methods that reduce these high-dimensional representations into latent low-dimensional structures that are discriminative and/or predictive of behavior, disease, or in general experimental context. We propose a metric learning framework to extract meaningful latent structures from high-dimensional fMRI data. This method learns the latent embeddings that reduce the intra-group variability while maximizing the inter-group variability. In addition, our method leverages advances in few-shot learning approaches to adapt to small sample-size fMRI datasets, allowing one to learn the latent structure from just a few samples per context. We evaluate our work on two publicly available fMRI datasets and report superior results compared to popular alternative approaches such as Principal Component Analysis (84.7% vs. 60%; 21.8% vs. 8.3%). We provide the Python code as open-source at Github.
Reconciling ASPP-p53 Binding Mode Discrepancies through an Ensemble Binding Framework that Bridges Crystallography and NMR Data
Authors: Liu Te , Huang Sichao , Zhang Qian , Xia Yu , Zhang Manjie , Sun Bin 
Published: September 2023

AbstractASPP2 and iASPP bind to p53 through their conserved ANK-SH3 domains to respectively promote and inhibit p53-dependent cell apoptosis. While crystallography has indicated that these two proteins employ distinct surfaces of their ANK-SH3 domains to bind to p53, solution NMR data has suggested similar surfaces. In this study, we employed multi-scale molecular dynamics (MD) combined with free energy calculations to reconcile the discrepancy in the binding modes. We demonstrated that the binding mode based solely on a single crystal structure does not enable iASPP’s RT loop to engage with p53’s C-terminal linker—a verified interaction. Instead, an ensemble of simulated iASPP-p53 complexes facilitates this interaction. We showed that the ensemble-average inter-protein contacting residues and NMR-detected interfacial residues align well with ASPP proteins, and the ensemble-average binding free energies better match experimental Kd values compared to single crystallgarphy-determined binding mode. For iASPP, the sampled ensemble complexes can be grouped into two classes, resembling the binding modes determined by crystallography and solution NMR. We thus propose that crystal packing shifts the equilibrium of binding modes towards the crystallographydetermined one. Lastly, we show that the ensemble binding complexes are sensitive to p53’s intrinsically disordered regions (IDRs), attesting to experimental observations that these IDRs contribute to biological functions. Our results provide a dynamic and ensemble perspective for scrutinizing these important cancer-related protein-protein interactions (PPIs).
Adherence Behaviors to Prevent COVID: The Role of Anxiety and Prosocial Behaviors
Authors: Corbera Silvia , Marín-Chollom Amanda M. 
Published: September 2023

AbstractObjectiveIn situations of acute stress, individuals may engage in prosocial behaviors or alternatively, individuals may engage in risk taking self-oriented behaviors. The COVID-19 pandemic created large stress-promoting conditions that impacted individuals’ decisions to adhere to COVID-19 preventative behaviors. The aim of this study is to examine the relationship between anxiety during the pandemic and adherence behaviors to prevent the spread of COVID-19, and the moderating influence prosocial behaviors.Method54 undergraduate students completed online questionnaires during the second wave of the pandemic: prosocial behaviors, anxiety, and COVID-19 preventive behaviors. Moderation analyses were conducted using Process in SPSS.ResultsResults demonstrated a statistically significant interaction of public prosocial behavior with state anxiety (β = -.17, p=.01) predicting engagement in COVID-19 preventative behaviors. At low levels of anxiety, low levels of prosocial public behaviors were associated with higher engagement in COVID-19 preventative behaviors. In contrast, high levels of public prosocial behavior were associated with lower engagement in COVID-19 preventative behaviors at low levels of anxiety.ConclusionResults provide information that can aid at in the creation of anxiety reducing interventions that could increase adherence to COVID-19 preventative behaviors.
The Impact of the President’s Emergency Program for AIDS Relief (PEPFAR) on Children
Authors: Stover John , Flanagan Clare F. , Teng Yu 
Published: September 2023

AbstractBackgroundThe AIDS epidemic has had severe impacts on children causing 7.7 million child deaths and orphaning 15 million children. The impact would have been even greater if the PEPFAR program had not provided drugs and services to avert millions of new infections and AIDS-related deaths. This paper estimates the historical impact of PEPFAR support on children and projects the impact through 2030 if the PEPFAR program were to stop in 2024.MethodsWe used the Goals RSM HIV simulation model to project counterfactual scenarios of no PEPFAR support during both the historical period (2000-2022) and the future period (2024-2030). We applied the model to 53 countries receiving PEPFAR support.ResultsFrom 2004-2022 the PEPFAR program averted 2.8 million new child HIV infections, 1.5 million child HIV-related deaths and prevented 8.2 million children from becoming AIDS orphans. A continuation of PEPFAR at its current level through 2030 would avert one million new child HIV infections, 460,000 child HIV-related deaths and 2.8 million AIDS orphans.DiscussionThe PEPFAR program has been crucial to the success that has been achieved to date in the global fight against AIDS. That success has created an obligation. Continuation of PEPFAR is critical to the effort to achieve the end of AIDS in the coming years.
A Common Data Model for the standardization of intensive care unit (ICU) medication features in artificial intelligence (AI) applications
Authors: Sikora Andrea , Keats Kelli , Murphy David J. , Devlin John W. , Smith Susan E. , Murray Brian , Buckley Mitchell S. , Rowe Sandra , Coppiano Lindsey , Kamaleswaran Rishikesan 
Published: September 2023

AbstractObjectiveCommon Data Models provide a standard means of describing data for artificial intelligence (AI) applications, but this process has never been undertaken for medications used in the intensive care unit (ICU). We sought to develop a Common Data Model (CDM) for ICU medications to standardize the medication features needed to support future ICU AI efforts.Materials and MethodsA 9-member, multi-professional team of ICU clinicians and AI experts conducted a 5-round modified Delphi process employing conference calls, web-based communication, and electronic surveys to define the most important medication features for AI efforts. Candidate ICU medication features were generated through group discussion and then independently scored by each team member based on relevance to ICU clinical decision-making and feasibility for collection and coding. A key consideration was to ensure the final ontology both distinguished unique medications and met Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles.ResultsUsing a list of 889 ICU medications, the team initially generated 106 different medication features, and 71 were ranked as being core features for the CDM. Through this process, 106 medication features were assigned to two key feature domains: drug product-related (n=43) and clinical practice-related (n=63). Each feature included a standardized definition and suggested response values housed in the electronic data library. This CDM for ICU medications is available online.DiscussionThe CDM for ICU medications represents an important first step for the research community focused on exploring how AI can improve patient outcomes and will require ongoing engagement and refinement.Lay SummaryMedication data pose a unique challenge for interpretation by artificial intelligence (AI) because of the alphanumerical combinations (e.g., ibuprofen 200mg every 4 hours) and because of the technical detail associated with drug prescriptions (e.g., ibuprofen 200mg and acetaminophen 325mg are both starting doses and round tablet sizes, so it would be incorrect for the machine to view 325mg as ‘more’ than 200mg). Because AI has great potential to improve the safety and efficacy of medication use, a common data model for ICU medications (ICURx) is proposed here to overcome these challenges and support AI efforts in medication analysis.