bluuebunny/crossref_metadata_2025_split huggingface dataset:
Psychiatric Symptoms Across the Menstrual Cycle in Adult Women: A Comprehensive Review
Authors: Handy Ariel B. , Greenfield Shelly F. , Yonkers Kimberly A. , Payne Laura A. 
Published: March 2022

Learning objective
After participating in this activity, learners should be better able to:
• Discuss and outline the general and overlapping effects of the menstrual cycle on women’s mental health

Abstract
A growing body of research demonstrates menstrual cycle–dependent fluctuations in psychiatric symptoms; these fluctuations can therefore be considered as prevalent phenomena. Possible mechanisms underlying these fluctuations posit behavioral, psychological, and neuroendocrine influences. Recent reviews document cyclic exacerbation of symptoms and explore these mechanisms in the context of specific and often single disorders. The question remains, however, as to whether there are general and overlapping effects of the menstrual cycle on women’s mental health. To address this gap, we synthesized the literature examining the exacerbation of a variety of psychiatric symptoms across the menstrual cycle in adult women. Results show that the premenstrual and menstrual phases are most consistently implicated in transdiagnostic symptom exacerbation. Specifically, strong evidence indicates increases in psychosis, mania, depression, suicide/suicide attempts, and alcohol use during these phases. Anxiety, stress, and binge eating appear to be elevated more generally throughout the luteal phase. The subjective effects of smoking and cocaine use are reduced during the luteal phase, but fewer data are available for other substances. Less consistent patterns are demonstrated for panic disorder, symptoms of posttraumatic stress disorder, and borderline personality disorder, and it is difficult to draw conclusions for symptoms of generalized anxiety disorder, social anxiety disorder, obsessive-compulsive disorder, and trichotillomania because of the limited data. Future research should focus on developing standardized approaches to identifying menstrual cycle phases and adapting pharmacological and behavioral interventions for managing fluctuations in psychiatric symptoms across the menstrual cycle.
Brolucizumab for the treatment of diabetic macular edema
Authors: Kuo Blanche L. , Singh Rishi P. 
Published: March 2022

Purpose of review
To review the available data supporting the use of brolucizumab in the treatment of diabetic macular edema (DME).

Recent findings
Brolucizumab is a humanized single- chain variable antibody fragment (scFv), the smallest functional subunit of an antibody approved for intravitreal use. Three phase III studies demonstrate that at 52 weeks, brolucizumab has statistically superior anatomical outcomes of reducing retinal thickness (54.0–57.5% of brolucizumab treated eyes achieved central subfield thickness <280 μm compared to 40.1 – 41.4% of aflibercept treated eyes) and retinal fluid (present in 54.2–60.3% of brolucizumab treated eyes compared to 72.9–78.2% of aflibercept treated eyes). Brolucizumab also demonstrated a prolonged durability up to 16 weeks, thus reducing treatment burden. The visual outcomes appear noninferior to current anti-VEGF agents with an increased risk for intraocular inflammatory events (0.3–4.7% compared to 0.6–1.7%).

Summary
Results from recent phase III trials showing the efficacy and safety of brolucizumab presents an additional therapeutic option in the DME treatment landscape. It can reduce treatment burden in DME with increased inter-treatment intervals while conferring efficacy in both functional and anatomical outcomes. Caution should be taken regarding the risks of intraocular inflammation, retinal vasculitis, and retinal vascular occlusion.
Intramuscular Stem Cell Injection in Combination with Bioengineered Nerve Repair or Nerve Grafting Reduces Muscle Atrophy
Authors: Schaakxs Dominique , Wiberg Mikael , Kingham Paul J. , Kalbermatten Daniel F. 
Published: March 2022

Background:
Peripheral nerve injuries represent a clinical challenge, especially when they are accompanied by loss of neural tissue. In this study, the authors attempted to attain a better outcome after a peripheral nerve injury by both repairing the nerve lesion and treating the denervated muscle at the same time.

Methods:
Rat sciatic nerves were transected to create 10-mm gaps. Repair was performed in five groups (n = 5 rats for each), as follows: group 1, nerve repair using poly-3-hydroxybutyrate strips to connect the proximal and distal stumps, in combination with control growth medium injection in the gastrocnemius muscle; group 2, nerve repair with poly-3-hydroxybutyrate strip seeded with Schwann cell-like differentiated adipose stem cells (differentiated adipose stem cell strip) in combination with growth medium intramuscular injection; group 3, differentiated adipose stem cell strip in combination with intramuscular injection of differentiated adipose stem cells; group 4, repair using autograft (reverse sciatic nerve graft) in combination with intramuscular injection of growth medium; and group 5, autograft in combination with intramuscular injection of differentiated adipose stem cells. Six weeks after nerve injury, the effects of the stem cells on muscle atrophy were assessed.

Results:
Poly-3-hydroxybutyrate strips seeded with differentiated adipose stem cells showed a high number of βIII-tubulin–positive axons entering the distal stump and abundant endothelial cells. Group 1 animals exhibited more muscle atrophy than all the other groups, and group 5 animals had the greatest muscle weights and muscle fibers size.

Conclusion:
Bioengineering nerve repair in combination with intramuscular stem cell injection is a promising technique to treat nerve lesions and associated muscle atrophy.

Clinical Relevance Statement:
Nerve injuries and resulting muscle atrophy are a clinical challenge. To optimize functional recovery after a nerve lesion, the authors treated the nerve and muscle at the same time by using regenerative medicine with adipose stem cells and obtained encouraging results for future clinical applications.
Procurement of Deceased Donor Parathyroid Glands With the Aid of Near-infrared Autofluorescence Imaging
Authors: Ward Casey J. , Kelly Yvonne M. , Syed Shareef M. , Meier Raphael P.H. , Ando Tadasuke , Wisel Steven A. , Gardner James M. , Stock Peter G. , Duh Quan-Yang 
Published: March 2022

Background.
Parathyroid allotransplantation is a burgeoning treatment for severe hypoparathyroidism. Deceased donor parathyroid gland (PTG) procurement can be technically challenging due to lack of normal intraoperative landmarks and exposure constraints in the neck of organ donors. In this study, we assessed standard 4-gland exposure in situ and en bloc surgical techniques for PTG procurement and ex vivo near-infrared autofluorescence (NIRAF) imaging for identification of PTGs during organ recovery.

Methods.
Research tissue consent was obtained from organ donors or donor families for PTG procurement. All donors were normocalcemic, brain-dead, solid organ donors between 18 and 65 y of age. PTGs were procured initially using a standard 4-gland exposure technique in situ and subsequently using a novel en bloc resection technique after systemic organ preservation flushing. Parathyroid tissue was stored at 4 °C in the University of Wisconsin solution up to 48 h post-procurement. Fluoptics Fluobeam NIRAF camera and Image J software were utilized for quantification of NIRAF signal.

Results.
Thirty-one brain-dead deceased donor PTG procurements were performed by abdominal transplant surgeons. In the initial 8 deceased donors, a mean of 1.75 glands (±1.48 glands SD) per donor were recovered using the 4-gland in situ technique. Implementation of combined en bloc resection with ex vivo NIRAF imaging in 23 consecutive donors yielded a mean of 3.60 glands (±0.4 SD) recovered per donor (P < 0.0001). Quantification of NIRAF integrated density signal demonstrated >1-fold log difference in PTG (2.13 × 105 pixels) versus surrounding anterior neck structures (1.9 × 104 pixels; P < 0.0001). PTGs maintain distinct NIRAF signal from the time of recovery (1.88 × 105 pixels) up to 48 h post-procurement (1.55 × 105 pixels) in organ preservation cold storage (P = 0.34).

Conclusions.
The use of an en bloc surgical technique with ex vivo NIRAF imaging significantly enhances the identification and recovery of PTG from deceased donors.
Effect of a Pilates exercise program on the flexion-relaxation rate in women with chronic low back pain
Authors: Ferri-Caruana Ana , Romagnoli Marco , Salazar-Bonet Lluis Raimon , Staiano Walter 
Published: March 2022

AbstractPurposeTo evaluate the effect of a Pilates exercise program (PEP) on FRR and FRR asymmetry of the erector spinae (ES) muscle during standing maximal trunk flexion/extension in women with chronic low-back pain (LBP). A secondary goal was to investigate the effect of PEP on full trunk flexion ROM (TFRoM), pain intensity and functional capacity and analyse their relationship with the FRR.Material and methodsThirty women with chronic LPB were randomly assigned to either PEP (EG, n=15) or control group (CG=15). EG followed an 8-week PEP while no specific intervention was carried out on the controls. Before and after this period all variables were recorded.ResultsFRR did not show any significant changes between or within groups (p>0.05). EG showed a significant statistical difference in the FRR asymmetry pre- and post-intervention (p□ 0.05). Full TFRoM did not show any significant changes between or within groups (p>0.05). EG showed a significant decrease of 30% on pain intensity and a significant increase of 13.4 % in functional capacity (P□0.001) from pre to post-intervention.ConclusionsAn 8-week PEP does not affect FRR nor full trunk ROM, however yields improvements in pain intensity and functional capacity.Professionals should be aware of the negative effect on FRR asymmetry.
Predicting pneumothorax after lung biopsy from pre-operative imaging using a deep convolutional neural network
Authors: Jang Seong Jun , Pua Bradley B. , Shih George 
Published: March 2022

AbstractBackgroundPneumothorax remains one of the most common complications after computed tomography (CT)–guided lung biopsies. Radiographic features including bullae and nodule size are possible markers for post-biopsy pneumothorax. We determine whether a convolutional neural network (CNN) can accurately predict a pneumothorax after lung biopsy based on pre-operative imaging alone.MethodsWith institutional review board approval, we retrospectively evaluated 3,822 patients who underwent a CT-guided lung biopsy between 2011 to 2019. Two image sets were created with CT scout images (1300 patients, 650 pneumothoraces) and chest x-rays (CXR) taken within three months pre-procedure (884 patients, 140 pneumothoraces). Using pre-operative images, CNNs of varying layer depths were trained using transfer learning to predict the development of a pneumothorax post-biopsy. Performance against models were compared using sensitivity analysis and the McNemar’s test.ResultsThe CNN models trained with CT scout images performed near chance. However, the models performed better with CXR radiographs taken within three months pre-biopsy. For the anterior-posterior view, sensitivity was 0.40, specificity was 0.89, PPV was 0.43, and NPV was 0.87 (AUC = 0.67). For the lateral view, sensitivity was 0.40, specificity was 0.80, PPV was 0.32, and NPV was 0.86 (AUC = 0.65). Increasing CNN layers did not affect performance (p > 0.05).ConclusionChest radiographs taken within three months of lung biopsy may provide important radiographic information for CNNs to assess pneumothorax risk in patients prior to CT-guided lung biopsies. However, more baseline and standardized CXRs before biopsies are necessary to create a robust model for clinical application.
The clinical need for clustered AChR cell-based assay testing of seronegative MG
Authors: Masi Gianvito , Li Yingkai , Karatz Tabitha , Pham Minh C. , Oxendine Seneca R. , Nowak Richard J. , Guptill Jeffrey T. , O’Connor Kevin C. 
Published: March 2022

AbstractTrial eligibility in myasthenia gravis (MG) remains largely dependent on a positive autoantibody serostatus. This significantly hinders seronegative MG (SNMG) patients from receiving potentially beneficial new treatments. In a subset of SNMG patients, acetylcholine receptor (AChR) autoantibodies are detectable by a clustered AChR cell-based assay (CBA). Of 99 SNMG patients from two academic U.S. centers, 18 (18.2%) tested positive by this assay. Autoantibody positivity was further validated in 17/18 patients. In a complementary experiment, circulating AChR-specific B cells were identified in a CBA-positive SNMG patient. These findings corroborate the clinical need for clustered AChR CBA testing when evaluating SNMG patients.
A Genomic Snapshot of Enterococcus faecalis within Public Hospital Environments in South Africa
Authors: Shobo Christiana O. , Amoako Daniel G. , Allam Mushal , Ismail Arshad , Essack Sabiha Y. , Bester Linda A. 
Published: March 2022

AbstractEnterococci are among the most common opportunistic hospital pathogens. This study used whole-genome sequencing (WGS) and bioinformatics to determine the antibiotic resistome, genetic support, clones and phylogenetic relationship of Enterococcus faecalis isolated from hospital environments in South Africa. Isolates were recovered from 11 frequently touched sites by patients and healthcare workers in different wards at 4 levels of healthcare (A, B, C and D) in Durban, South Africa. Following microbial identification and antibiotic susceptibility tests. Of the 245 E. faecalis isolates identified, 38 were subjected to WGS on the Illumina MiSeq platform. The tet(M) (31/38, 82%) and erm(C) (16/38, 42%) genes were the most common antibiotic resistome found in isolates originating from the different hospital environments which corroborated with their antibiotic resistance phenotypes. The isolates harboured mobile genetic elements consisting of plasmids (n=11) and prophages (n=14), that were mostly clone-specific. Of note, a large number insertion sequence (IS) families were found with the IS3 (55%), IS5 (42%), IS1595 (40%) and Tn3 Transposon been the most predominate. Microbial typing using WGS data revealed 15 clones with 6 major sequence types (ST) belonging to ST16 (n =7), ST40 (n = 6), ST21 (n =5), ST126 (n = 3), ST23 (n =3) and ST386 (n=3). Phylogenomic analysis showed that the major clones were mostly conserved within specific hospital environments. However, further metadata insights revealed the complex intra-clonal spread of these E. faecalis major clones between the sampling sites within each specific hospital setting. The results of these genomic analyses will offer insights into E. faecalis in the hospital environments relevant in the design of optimal infection prevention strategies in hospital settings.
Processing Stage Flexibility of the SNARC effect: Task Relevance or Magnitude Relevance?
Authors: Xiang Xinrui , Yan Lizhu , Fu Shimin , Nan Weizhi 
Published: March 2022

AbstractPrevious studies have shown that the processing stage of the spatial-numerical association of response codes (SNARC) effect was flexible. Two recent studies by Nan et al. (2021) and Yan et al. (2021) used the same experimental paradigm to check whether the SNARC effect occurred in the semantic-representation stage but reached contradictory conclusions, showing that the SNARC effect was influenced by a magnitude Stroop effect in a magnitude comparison task but not by a parity Stroop effect in a parity judgment task. The two studies had two distinct operational factors: the task type (magnitude comparison task or parity judgment task, with the numerical magnitude information task-relevant or task-irrelevant) and the semantic representation stage-related interference information (magnitude or parity Stroop effect, with the interference information magnitude-relevant or magnitude-irrelevant). To determine which factor influenced the SNARC effect, in the present study, the Stroop effect was switched in the two tasks based on the previous studies. The findings of four experiments consistently showed that the SNARC effect was not influenced by the parity Stroop effect in the magnitude comparison task but was influenced by the magnitude Stroop effect in the parity judgment task. Combined with the results of Nan et al. (2021) and Yan et al. (2021), the findings indicated that regardless of the task type or the task-relevance of numerical magnitude information, magnitude-relevant interference information was the primary factor to affect the SNARC effect. Furthermore, a two-stage processing model that explained the observed flexibility of the SNARC effect was proposed and discussed.Public Significance StatementPrevious studies have shown that the spatial-numerical association of response codes (SNARC) effect is flexible in the direction and processing stage. The task type and interference information might be two influential factors for the flexibility of the SNARC effect. The present study reported that magnitude-relevant interference information, regardless of task type, was a crucial role to affect the SNARC effect. Moreover, a two-stage processing model was proposed to reveal the processing pathway of the SNARC effect and provided a possible explanation for the longstanding debate about the processing stage of the SNARC effect.
The transcription factor network of E. coli steers global responses to shifts in RNAP concentration
Authors: Almeida Bilena L B , Bahrudeen Mohamed N M , Chauhan Vatsala , Dash Suchintak , Kandavalli Vinodh , Häkkinen Antti , Lloyd-Price Jason , Palma Cristina S D , Baptista Ines S C , Gupta Abhishekh , Kesseli Juha , Dufour Eric , Smolander Olli-Pekka , Nykter Matti , Auvinen Petri , Jacobs Howard T , Oliveira Samuel M D , Ribeiro Andre S 
Published: March 2022

ABSTRACTThe robustness and sensitivity of gene networks to environmental changes is critical for cell survival. How gene networks produce specific, chronologically ordered responses to genome-wide perturbations, while robustly maintaining homeostasis, remains an open question. We analysed if short- and mid-term genome-wide responses to shifts in RNA polymerase (RNAP) concentration are influenced by the known topology and logic of the transcription factor network (TFN) of Escherichia coli. We found that, at the gene cohort level, the magnitude of the single-gene, mid-term transcriptional responses to changes in RNAP concentration can be explained by the absolute difference between the gene’s numbers of activating and repressing input transcription factors (TFs). Interestingly, this difference is strongly positively correlated with the number of input TFs of the gene. Meanwhile, short-term responses showed only weak influence from the TFN. Our results suggest that the global topological traits of the TFN of E. coli shape which gene cohorts respond to genome-wide stresses.
Integrative analysis to identify shared mechanisms between schizophrenia and bipolar disorder and their comorbidities
Authors: Bharadhwaj Vinay Srinivas , Mubeen Sarah , Sargsyan Astghik , Jose Geena Mariya , Geissler Stefan , Hofmann-Apitius Martin , Domingo-Fernández Daniel , Kodamullil Alpha Tom 
Published: March 2022

AbstractSchizophrenia and bipolar disorder are characterized by highly similar neuropsychological signatures, implying shared neurobiological mechanisms between these two disorders. These disorders also have comorbidities with other indications, such as type 2 diabetes mellitus (T2DM). To date, an understanding of the mechanisms that mediate the link between these two disorders remains incomplete. In this work, we identify and investigate shared patterns across multiple schizophrenia, bipolar disorder and T2DM gene expression datasets through multiple strategies. Firstly, we investigate dysregulation patterns at the gene-level and compare our findings against disease-specific knowledge graphs (KGs). Secondly, we analyze the concordance of co-expression patterns across datasets to identify disease-specific as well as common pathways. Thirdly, we examine enriched pathways across datasets and disorders to identify common biological mechanisms between them. Lastly, we investigate the correspondence of shared genetic variants between these two disorders and T2DM as well as the disease-specific KGs. In conclusion, our work reveals several shared candidate genes and pathways, particularly those related to the immune and nervous systems, which we propose mediate the link between schizophrenia and bipolar disorder and its shared comorbidity, T2DM.
Community structure determines the predictability of population collapse
Authors: Baruah Gaurav , Ozgul Arpat , Clements Christopher F. 
Published: March 2022

AbstractEarly warning signals (EWS) are phenomenological tools that have been proposed as predictors of the collapse of biological systems. Whilst a growing body of work has shown the utility of EWS based on either statistic derived from abundance data or shifts in phenotypic traits such as body size, so far this work has largely focused on single species populations.However, in order to predict reliably the future state of ecological systems which inherently could consist of multiple species, understanding how reliable such signals are in a community context is critical.Here, reconciling quantitative genetics and Lotka-Volterra equations which allow us to track both abundance and mean traits, we simulate the collapse of populations embedded in mutualistic and multi-trophic predator-prey communities. Using these simulations and warning signals derived from both population- and community-level data, we show that the utility of abundance-based EWS as well as metrics derived from stability-landscape theory (e.g., width and depth of the basin of attraction) are fundamentally linked, and thus the depth and width of the stability landscape could be used to identify which species should exhibit the strongest EWS of collapse.The probability a species displays both trait and abundance based EWS is dependent on its position in a community, with some species able to act as indicators species. In addition, our results also demonstrate that in general trait-based EWS appear less reliable in comparison to abundance-based EWS in forecasting species collapses in our simulated communities. Furthermore, community-level abundance-based EWS were fairly reliable in comparison to their species-level counterparts in forecasting species level collapses.Our study suggests a holistic framework that combines abundance-based EWS and metrics derived from stability-landscape theory that may help in forecasting species loss in a community context.