Is endometriosis typology a potentially better classification system for assessing risk of female infertility?

Objective: To determine whether endometriosis typology, namely ovarian endometriomas (OE), deep infiltrating endometriosis (DIE), or superficial endometriosis (SE), correlates with fertility history.

Design: Prospective cohort.

Setting: One of fourteen surgical centers in Salt Lake City, Utah (n = 5) or San Francisco, California (n = 9).

Treatment of pneumothorax and bronchopleural fistula by extracorporeal membrane oxygenation in a neonate: a case report.

Intractable pneumothorax secondary to bronchopulmonary fistula is a rare complication in neonates. We present the first report of a newborn with spontaneous pneumothorax and bronchopleural fistula treated with extracorporeal membrane oxygenation (ECMO). Positive pressure mechanical ventilation resulted in persistent air leakage from the bronchopleural fistula.

Constructing Strong and Tough Polymer Elastomers via Photoreversible Coumarin Dimer Mechanophores.

Advanced elastomers with outstanding strength, toughness, and reusability hold significant potential for diverse applications. Using photochemistry and mechanochemistry to develop such materials has become a very effective strategy. Here, we report that photoreversible coumarin-based mechanophores that can make force-/light-triggered cycloreversion are chemically incorporated into polyurethane elastomers to simultaneously enhance their strength and toughness.

A cross-attention swin transformer network for EEG-based subject-independent cognitive load assessment.

Unlabelled: EEG signals play a crucial role in assessing cognitive load, which is a key element in ensuring the secure operation of human-computer interaction systems. However, the variability of EEG signals across different subjects poses a challenge in applying the pre-trained cognitive load assessment model to new subjects. Moreover, previous domain adaptation research has primarily focused on developing complex network architectures to learn more domain-invariant features, overlooking the noise introduced by pseudo-labels and the challenges posed by domain migration problems.

A reconstruction method for ptychography based on residual dense network.

Background: Coherent diffraction imaging (CDI) is an important lens-free imaging method. As a variant of CDI, ptychography enables the imaging of objects with arbitrary lateral sizes. However, traditional phase retrieval methods are time-consuming for ptychographic imaging of large-size objects, e.

Mediating role of immune cells in association between volatile organic compounds and periodontitis: NHANES 2011-2014.

Background: The relationship between humans and volatile organic compounds (VOCs) is a persistent concern due to their widespread sources and high evaporation rates. However, there is currently limited direct evidence linking VOC exposure to the development of periodontitis.

Methods: This cross-sectional study analyzed 1525 participants and 21 urinary VOCs in the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2014, aiming to investigate the relationship between periodontitis risk, assessed by attachment loss (AL) and probing depth (PD) and individual VOCs using logistic regression, quantile regression, and subgroup analysis.

Design and validation of a real-time cassava planter seed quality monitoring system based on optical fiber sensors and rotary encoders.

Targeting the issues of seed leakage and cutting segment adhesion due to poor seed feeding and cutting in real-time seed-cutting cassava planters, this study developed a seeding quality monitoring system. Based on the structure and working principle of the seed cutting and discharging device, the installation methods of the matrix fiber optic sensor and rotary encoder were determined. By combining the operational characteristics of the planter's ground wheel drive with seed cutting and seed dropping, a monitoring model correlating the sowing parameters with seed dropping time was established; a monitoring window was created by extracting and processing the rotary encoder pulse signal, and the number of seeds sown after each opposing cutter's operation was calculated based on the pulse width information within the monitoring window.

3-Dimensional quantitative analysis of mandibular motion in TMD and healthy subjects: Comparison with clinical observations.

Objectives: To establish a quantitative method for objectively assessing 3-dimensional (3D) mandibular trajectories and comparing clinical evaluations with computational analyses.

Methods: In total, 184 volunteers were recruited and grouped into control (n = 121) and temporomandibular disorder (TMD) groups (n = 63) according to the dual-axis DC/TMD checklist. 3D trajectories were generated by integrating mandibular motion and cone beam computed tomography (CBCT) records.

A self-attention-driven deep learning framework for inference of transcriptional gene regulatory networks.

The interactions between transcription factors (TFs) and the target genes could provide a basis for constructing gene regulatory networks (GRNs) for mechanistic understanding of various biological complex processes. From gene expression data, particularly single-cell transcriptomic data containing rich cell-to-cell variations, it is highly desirable to infer TF-gene interactions (TGIs) using deep learning technologies. Numerous models or software including deep learning-based algorithms have been designed to identify transcriptional regulatory relationships between TFs and the downstream genes.

A novel method of cognitive overload assessment based on a fusion feature selection using EEG signals.

Cognitive overload, as an overload state of cognitive workload, negatively impacts individuals' task performance and mental health. Cognitive overload assessment models based on Electroencephalography (EEG) can effectively prevent the occurrence of overload through early warning, thereby enhancing task execution efficiency and safeguarding individuals' mental health. Although existing EEG-based cognitive load assessment methods have achieved significant research outcomes, evaluating cognitive overload remains an ongoing challenge.

A new genus of tribe Dikraneurini (Hemiptera: Cicadellidae: Typhlocybinae) from China based on a new species and genus checklist from China provided.

A new leafhopper genus Sugea gen. nov. is described and illustrated here based on type species Sugea obtusangula sp.

A new genus and three new species of Empoascini (Hemiptera: Cicadellidae: Typhlocybinae) from China.

One new genus and three new species of Empoascini from China are described and illustrated: Ventriappendix Ding, Yu & Yang gen. nov. with a new species V.

Assessment of primary school in Changsha based on AISM method.

To tackle the challenge of a one-size-fits-all and inconsistent approach to evaluating school development across districts, we have zeroed in on five key urban districts in Changsha City. Fourteen secondary indicators, spanning four critical categories - campus environment, teaching facilities, financial investment, and teacher resources - were selected to comprehensively assess the development of elementary schools in 2021. This assessment was conducted using the Advanced Interpretive Structural Model (AISM).

Parametric tuning of quantum phase transitions in ultracold reactions.

Advances in atomic physics have led to the possibility of a coherent transformation between ultracold atoms and molecules including between completely bosonic condensates. Such transformations are enabled by the magneto-association of atoms at a Feshbach resonance which results in a passage through a quantum critical point. In this study, we show that the presence of generic interaction between the constituent atoms and molecules can fundamentally alter the nature of the critical point, change the yield of the reaction and the order of the consequent phase transition.

Porcine decellularized nerve matrix hydrogel attenuates neuroinflammation after peripheral nerve injury by inhibiting the TLR4/MyD88/NF-κB axis.

Peripheral nerve injury causes severe neuroinflammation and has become a global medical challenge. Previous research has demonstrated that porcine decellularized nerve matrix hydrogel exhibits excellent biological properties and tissue specificity, highlighting its potential as a biomedical material for the repair of severe peripheral nerve injury; however, its role in modulating neuroinflammation post-peripheral nerve injury remains unknown. Here, we aimed to characterize the anti-inflammatory properties of porcine decellularized nerve matrix hydrogel and their underlying molecular mechanisms.

TPepPro: a deep learning model for predicting peptide-protein interactions.

Motivation: Peptides and their derivatives hold potential as therapeutic agents. The rising interest in developing peptide drugs is evidenced by increasing approval rates by the FDA of USA. To identify the most potential peptides, study on peptide-protein interactions (PepPIs) presents a very important approach but poses considerable technical challenges.

Generation of arbitrary vector orbital angular momentum beams on higher-order Poincaré spheres based on an all-dielectric metasurface with complex amplitude modulation.

Vector orbital angular momentum (OAM) beams, described by higher-order Poincaré (HOP) sphere, are generalized forms of waves carrying OAM with an inhomogeneous polarization of wavefronts. We construct all-dielectric metasurfaces with adjustable amplitude, polarization, and phase to generate arbitrary vector OAM beams. The metasurface is composed of two pairs of silicon nanopillars arranged alternately.

Development of a nomogram based on whole-tumor multiparametric MRI histogram analysis to predict deep myometrial invasion in stage I endometrioid endometrial carcinoma preoperatively.

Background: The depth of myometrial invasion determines whether International Federation of Gynecology and Obstetrics stage I endometrioid endometrial carcinoma (EEC) patients undergo lymph node dissection. However, subjective evaluation results relying on magnetic resonance imaging (MRI) are not always satisfactory.

Purpose: To develop a nomogram based on whole-volume tumor MRI histogram parameters to preoperatively predict deep myometrial invasion (DMI) in patients with stage I EEC.

An fMRI dataset in response to large-scale short natural dynamic facial expression videos.

Facial expression is among the most natural methods for human beings to convey their emotional information in daily life. Although the neural mechanisms of facial expression have been extensively studied employing lab-controlled images and a small number of lab-controlled video stimuli, how the human brain processes natural dynamic facial expression videos still needs to be investigated. To our knowledge, this type of data specifically on large-scale natural facial expression videos is currently missing.

Network pharmacology analysis and clinical verification of saponins in deep venous thrombosis prevention.

In the present study, the mechanism of saponins (PNS), the extract of , against deep vein thrombosis (DVT) was explored by networks pharmacology and its effect was demonstrated through clinical data. PNS includes 5 main active components, which have 101 targets. A total of 1,342 DVT-related targets were obtained, 55 of which were the common targets of PNS and DVT.

Thermally regulated flocculation-coalescence process by temperature-responsive cationic polymeric surfactant for enhanced crude oil-water separation.

Polymeric surfactants play a crucial role in the flocculation-assisted coalescence process due to their unique bridging effect. However, the steric hindrance induced by their large molecules severely impedes the coalescence of oil droplets. Herein, temperature-responsive polymeric surfactants (quaternary ammonium chitosan-g-PNIPAM, Q-g-PN) with thermally-modulated structure were designed by integrating thermal responsive moieties onto cationic chitosan.