bluuebunny/crossref_metadata_2025 huggingface dataset:
PD-(L)1 inhibitors plus bevacizumab and chemotherapy as first-line therapy in PD-L1-negative metastatic lung adenocarcinoma: a real-world data
Authors: Ge Yihui , Zhan Yujing , He Jie , Li Juan , Wang Jian , Wei Xiaojuan , Wang Chunni , Gao Aiqin , Sun Yuping
Published: March 2024

Background

Chemotherapy combined with immune checkpoint inhibitors (IC), bevacizumab (BC), or both (IBC) is the preferred first-line therapy for PD-L1-negative and oncogenic-driver wild-type metastatic lung adenocarcinoma. However, the optimal strategy is still undetermined.

Methods

This retrospective study enrolled PD-L1-negative metastatic lung adenocarcinoma patients from four cancer centers between January 1, 2018 and June 30, 2022. All the patients received IC, BC, or IBC as the first-line therapies. The efficacy and safety were evaluated.

Results

A total of 205 patients were included, with 60, 83, and 62 patients in IC, BC, and IBC groups, respectively. The baseline characteristics among three groups were well balanced. Patients treated with IBC had the highest objective response rate (ORR) (43.5%) and disease control rate (DCR) (100%) relative to those treated with IC (40.4%, 84.2%) or BC (40.5%, 96.2%) (ORR: P = 0.919, DCR: P < 0.01). Compared with the IC (6.74 m) or BC (8.28 m), IBC treatment significantly improved median progression-free survival (mPFS) (9.53 m, P = 0.005). However, no difference in overall survival (OS) was observed. When stratified by different clinical and molecular information, we found that male gender, ever smoking, wild-type genes mutations, and adrenal metastasis predict superior PFS benefit when treated with IBC. In patients with liver metastasis, IBC or BC treatment displayed better PFS compared with IC. No additional adverse reactions were observed in IBC group compared with other two groups.

Conclusion

Combined IBC treatment achieved superior DCR and PFS compared with IC or BC in patients with PD-L1-negative metastatic lung adenocarcinoma, while did not increase the adverse events.
Development strategy of non-GMO organism for increased hemoproteins in Corynebacterium glutamicum: a growth-acceleration-targeted evolution
Authors: Park Sehyeon , Lee Seungki , Kim Taeyeon , Choi Ahyoung , Lee Soyeon , Kim Pil
Published: March 2024

Heme, found in hemoproteins, is a valuable source of iron, an essential mineral. The need for an alternative hemoprotein source has emerged due to the inherent risks of large-scale livestock farming and animal proteins. Corynebacterium glutamicum, regarded for Qualified Presumption of Safety or Generally Recognized as Safe, can biosynthesize hemoproteins. C. glutamicum single-cell protein (SCP) can be a valuable alternative hemoprotein for supplying heme iron without adversely affecting blood fat levels. We constructed the chemostat culture system to increase hemoprotein content in C. glutamicum SCP. Through adaptive evolution, hemoprotein levels could be naturally increased to address oxidative stress resulting from enhanced growth rate. In addition, we used several specific plasmids containing growth-accelerating genes and the hemA promoter to expedite the evolutionary process. Following chemostat culture for 15 days, the plasmid in selected descendants was cured. The evolved strains showed improved specific growth rates from 0.59 h−1 to 0.62 h−1, 20% enhanced resistance to oxidative stress, and increased heme concentration from 12.95 µg/g-DCW to 14.22–15.24 µg/g-DCW. Notably, the putative peptidyl-tRNA hydrolase-based evolved strain manifested the most significant increase (30%) of hemoproteins. This is the first report presenting the potential of a growth-acceleration-targeted evolution (GATE) strategy for developing non-GMO industrial strains with increased bio-product productivity.
Analysis of factors influencing pancreatic fistula after minimally invasive pancreaticoduodenectomy and establishment of a new prediction model for clinically relevant pancreatic fistula
Authors: Zhu Yuwen , Wu Di , Yang Hao , Lu Zekun , Wang Zhiliang , Zu Guangchen , Li Zheng , Xu Xiaowu , Zhang Yue , Chen Xuemin , Chen Weibo
Published: March 2024

Background

Postoperative pancreatic fistula (POPF) is the most prevalent complications following minimally invasive pancreaticoduodenectomy (MIPD). Only one model related to MIPD exists, and previous POPF scoring prediction methods are based on open pancreaticoduodenectomy patients. Our objectives are to determine the variables that may increase the probability of pancreatic fistula following MIPD and to develop and validate a POPF predictive risk model.

Methods

Data from 432 patients who underwent MIPD between July 2015 and May 2022 were retrospectively collected. A nomogram prediction model was created using multivariate logistic regression analysis to evaluate independent factors for POPF in patients undergoing MIPD in the modeling cohort. The area under the curve (AUC) of the receiver operating characteristic curve (ROC) and the calibration curve were used to verify the nomogram prediction model internally and externally within the modeling cohort and the verification cohort.

Results

Multivariate logistic regression analysis showed that body mass index (BMI), albumin, triglycerides, pancreatic duct diameter, pathological diagnosis and intraoperative bleeding were independent variables for POPF. On the basis of this information, a model for the prediction of risks associated with POPF was developed. In accordance with the ROC analysis, the modeling cohort's AUC was 0.819 (95% CI 0.747–0.891), the internal validation cohort's AUC was 0.830 (95% CI 0.747–0.912), and the external validation cohort's AUC was 0.793 (95% CI 0.671–0.915). Based on the calibration curve, the estimated values of POPF have a high degree of concordance with the actual values that were measured.

Conclusions

This model for predicting the probability of pancreatic fistula following MIPD has strong predictive capacity and can provide a trustworthy predictive method for the early screening of high-risk patients with pancreatic fistula after MIPD and timely clinical intervention.
Comparing oncologic and surgical outcomes of robotic and laparoscopic pancreatoduodenectomy in patients with pancreatic cancer: a propensity-matched analysis
Authors: Wehrle Chase J. , Chang Jenny H. , Gross Abby R. , Woo Kimberly , Naples Robert , Stackhouse Kathryn A. , Dahdaleh Fadi , Augustin Toms , Joyce Daniel , Simon Robert , Walsh R. Matthew , Naffouje Samer A.
Published: March 2024

Introduction

Minimally invasive Pancreatoduodenectomy (MIPD), or the Whipple procedure, is increasingly utilized. No study has compared laparoscopic (LPD) and robotic (RPD) approaches, and the impact of the learning curve on oncologic, technical, and post-operative outcomes remains relatively understudied.

Methods

The National Cancer Database was queried for patients undergoing LPD or RPD from 2010 to 2020 with a diagnosis of pancreatic cancer. Outcomes were compared between approaches using propensity-score matching (PSM); the impact of annual center-level volume of MIPD was also assessed by dividing volume into quartiles.

Results

A total of 3,342 patients were included. Most (n = 2,716, 81.3%) underwent LPD versus RPD (n = 626, 18.7%). There was a high rate (20.2%, n = 719) of positive margins. Mean length-of-stay (LOS) was 10.4 ± 8.9 days. Thirty-day mortality was 2.8% (n = 92) and ninety-day mortality was 5.7% (n = 189).

PSM matched 625 pairs of patients receiving LPD or RPD. After PSM, there was no differences between groups based on age, sex, race, CCI, T-stage, neoadjuvant chemo/radiotherapy, or type of PD. After PSM, there was a higher rate of conversion to open (HR = 0.68, 95%CI = 0.50–0.92)., but there was no difference in LOS (HR = 1.00, 95%CI = 0.92–1.11), 30-day readmission (HR = 1.08, 95% CI = 0.68–1.71), 30-day (HR = 0.78, 95% CI = 0.39–1.56) or 90-day mortality (HR = 0.70, 95% CI = 0.42–1.16), ability to receive adjuvant therapy (HR = 1.15, 95% CI = 0.92–1.44), nodal harvest (HR = 1.01, 95%CI = 0.94–1.09) or positive margins (HR = 1.19, 95% CI = 0.89–1.59).

Centers in lower quartiles of annual volume of MIPD demonstrated reduced nodal harvest (p = 0.005) and a higher rate of conversion to open (p = 0.038). Higher-volume centers had a shorter LOS (p = 0.012), higher rate of initiation of adjuvant therapy (p = 0.042), and, most strikingly, a reduction in 90-day mortality (p = 0.033).

Conclusion

LPD and RPD have similar surgical and oncologic outcomes, with a lower rate of conversion to open in the robotic cohort. The robotic technique does not appear to eliminate the “learning curve”, with higher volume centers demonstrating improved outcomes, especially seen at minimum annual volume of 5 cases.
Grundzüge einer kritischen Medizinethik
Authors: Rubeis Giovanni
Published: March 2024

Die Medizinethik sieht sich zunehmend mit Herausforderungen konfrontiert, die sich aus gesellschaftlichen Machtasymmetrien und epistemischen Ungerechtigkeiten ergeben. Dabei fehlen der Medizinethik die epistemischen Linsen, um diese gesellschaftlichen Kontextfaktoren ärztlichen Handelns analysieren zu können. Um diesen Herausforderungen zu begegnen, bedarf es daher einer theoretisch-konzeptuellen Neuausrichtung. In diesem Beitrag werden die Grundzüge einer kritischen Medizinethik diskutiert, welche Perspektiven und Erkenntniskategorien aus kritischen Theorien übernimmt. Dazu gehört die Kritische Theorie der Frankfurter Schule sowie diejenigen Ansätze aus den Sozial- und Kulturwissenschaften, die auf Machtasymmetrien reflektieren. Dadurch soll das epistemische Spektrum der Medizinethik erweitert werden, um reale Machtverhältnisse besser in normative Analysen einbeziehen zu können.

In einem ersten Schritt wird der Beitrag der Sozialwissenschaften im Sinn einer empirischen Ethik diskutiert. Hierbei zeigt sich, dass eine empirische Ausrichtung alleine die epistemologische Lücke nicht schließen kann. In einem weiteren Schritt werden daher epistemische Linsen und Konzepte aus kritischen Theorien dargestellt. Dazu gehören einerseits die Kritische Theorie der Frankfurter Schule, andererseits feministische, postkoloniale, Queer- und Gender-Theorien sowie die Science and Technology Studies (STS). In einer Zusammenfassung werden die Grundzüge einer kritischen Medizinethik dargestellt und deren Limitierungen diskutiert.
Boolean Function Analysis on High-Dimensional Expanders
Authors: Dikstein Yotam , Dinur Irit , Filmus Yuval , Harsha Prahladh
Published: March 2024

We initiate the study of Boolean function analysis on high-dimensional expanders. We give a random-walk based definition of high-dimensional expansion, which coincides with the earlier definition in terms of two-sided link expanders. Using this definition, we describe an analog of the Fourier expansion and the Fourier levels of the Boolean hypercube for simplicial complexes. Our analog is a decomposition into approximate eigenspaces of random walks associated with the simplicial complexes. Our random-walk definition and the decomposition have the additional advantage that they extend to the more general setting of posets, encompassing both high-dimensional expanders and the Grassmann poset, which appears in recent work on the unique games conjecture. We then use this decomposition to extend the Friedgut–Kalai–Naor theorem to high-dimensional expanders. Our results demonstrate that a constant-degree high-dimensional expander can sometimes serve as a sparse model for the Boolean slice or hypercube, and quite possibly additional results from Boolean function analysis can be carried over to this sparse model. Therefore, this model can be viewed as a derandomization of the Boolean slice, containing only $$|X(k-1)|=O(n)$$

|
X
(
k
-
1
)
|
=
O
(
n
)

points in contrast to $$\left( {\begin{array}{c}n\\ k\end{array}}\right) $$

n

k

points in the (k)-slice (which consists of all n-bit strings with exactly k ones).
SHuffled Ant Lion Optimization approach with an exponentially weighted random walk strategy
Authors: Durgut Pinar G. , Tozak Mirac Bugse , Ayvaz M. Tamer
Published: March 2024

Ant Lion Optimization (ALO) method is one of the population-based nature-inspired optimization algorithms which mimics the hunting strategy of antlions. ALO is successfully employed for solving many complicated optimization problems. However, it is reported in the literature that the original ALO has some limitations such as the requirement of high number of iterations and possibility of trapping to local optimum solutions, especially for complex or large-scale problems. For this purpose, the SHuffled Ant Lion Optimization (SHALO) approach is proposed by conducting two improvements in the original ALO. Performance of the proposed SHALO approach is evaluated by solving some unconstrained and constrained problems for different conditions. Furthermore, the identified results are statistically compared with the ones obtained by using the original ALO, two improved ALOs which are the self-adaptive ALO (saALO) and the exponentially weighted ALO (EALO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) approaches. Identified results indicated that the proposed SHALO approach significantly improves the solution accuracy with a mean success rate of 76% in terms of finding the global or near-global optimum solutions and provides better results than ALO (22%), saALO (25%), EALO (14%), GA (28%), and PSO (49%) approaches for the same conditions.
Effectiveness and safety of primary prophylaxis with G-CSF after induction therapy for acute myeloid leukemia: a systematic review and meta-analysis of the clinical practice guidelines for the use of G-CSF 2022 from the Japan society of clinical oncology
Authors: Maeda Tomoya , Najima Yuho , Kamiyama Yutaro , Nakao Shinji , Ozaki Yukinori , Nishio Hiroshi , Tsuchihashi Kenji , Ichihara Eiki , Miumra Yuji , Endo Makoto , Maruyama Dai , Yoshinami Tatsuhiro , Susumu Nobuyuki , Takekuma Munetaka , Motohashi Takashi , Ito Mamoru , Baba Eishi , Ochi Nobuaki , Kubo Toshio , Uchino Keita , Kimura Takahiro , Tamura Shinobu , Nishimoto Hitomi , Kato Yasuhisa , Sato Atsushi , Takano Toshimi , Yano Shingo
Published: March 2024

Although granulocyte colony-stimulating factor (G-CSF) reduces the incidence, duration, and severity of neutropenia, its prophylactic use for acute myeloid leukemia (AML) remains controversial due to a theoretically increased risk of relapse. The present study investigated the effects of G-CSF as primary prophylaxis for AML with remission induction therapy. A detailed literature search for related studies was performed using PubMed, Ichushi-Web, and the Cochrane Library. Data were independently extracted and assessed by two reviewers. A qualitative analysis of pooled data was conducted, and the risk ratio with corresponding confidence intervals was calculated in the meta-analysis and summarized. Sixteen studies were included in the qualitative analysis, nine of which were examined in the meta-analysis. Although G-CSF significantly shortened the duration of neutropenia, primary prophylaxis with G-CSF did not correlate with infection-related mortality. Moreover, primary prophylaxis with G-CSF did not affect disease progression/recurrence, overall survival, or adverse events, such as musculoskeletal pain. However, evidence to support or discourage the use of G-CSF as primary prophylaxis for adult AML patients with induction therapy remains limited. Therefore, the use of G-CSF as primary prophylaxis can be considered for adult AML patients with remission induction therapy who are at a high risk of infectious complications.
Deep Learning Model for Prediction of Bronchopulmonary Dysplasia in Preterm Infants Using Chest Radiographs
Authors: Chou Hao-Yang , Lin Yung-Chieh , Hsieh Sun-Yuan , Chou Hsin-Hung , Lai Cheng-Shih , Wang Bow , Tsai Yi-Shan
Published: March 2024

Bronchopulmonary dysplasia (BPD) is common in preterm infants and may result in pulmonary vascular disease, compromising lung function. This study aimed to employ artificial intelligence (AI) techniques to help physicians accurately diagnose BPD in preterm infants in a timely and efficient manner. This retrospective study involves two datasets: a lung region segmentation dataset comprising 1491 chest radiographs of infants, and a BPD prediction dataset comprising 1021 chest radiographs of preterm infants. Transfer learning of a pre-trained machine learning model was employed for lung region segmentation and image fusion for BPD prediction to enhance the performance of the AI model. The lung segmentation model uses transfer learning to achieve a dice score of 0.960 for preterm infants with $$\le$$
≤
168 h postnatal age. The BPD prediction model exhibited superior diagnostic performance compared to that of experts and demonstrated consistent performance for chest radiographs obtained at $$\le$$
≤
24 h postnatal age, and those obtained at 25 to 168 h postnatal age. This study is the first to use deep learning on preterm chest radiographs for lung segmentation to develop a BPD prediction model with an early detection time of less than 24 h. Additionally, this study compared the model’s performance according to both NICHD and Jensen criteria for BPD. Results demonstrate that the AI model surpasses the diagnostic accuracy of experts in predicting lung development in preterm infants.
A review of predictive uncertainty estimation with machine learning
Authors: Tyralis Hristos , Papacharalampous Georgia
Published: March 2024

Predictions and forecasts of machine learning models should take the form of probability distributions, aiming to increase the quantity of information communicated to end users. Although applications of probabilistic prediction and forecasting with machine learning models in academia and industry are becoming more frequent, related concepts and methods have not been formalized and structured under a holistic view of the entire field. Here, we review the topic of predictive uncertainty estimation with machine learning algorithms, as well as the related metrics (consistent scoring functions and proper scoring rules) for assessing probabilistic predictions. The review covers a time period spanning from the introduction of early statistical (linear regression and time series models, based on Bayesian statistics or quantile regression) to recent machine learning algorithms (including generalized additive models for location, scale and shape, random forests, boosting and deep learning algorithms) that are more flexible by nature. The review of the progress in the field, expedites our understanding on how to develop new algorithms tailored to users’ needs, since the latest advancements are based on some fundamental concepts applied to more complex algorithms. We conclude by classifying the material and discussing challenges that are becoming a hot topic of research.
The distribution of breast density in women aged 18 years and older
Authors: Perera Dilukshi , Pirikahu Sarah , Walter Jane , Cadby Gemma , Darcey Ellie , Lloyd Rachel , Hickey Martha , Saunders Christobel , Hackmann Michael , Sampson David D. , Shepherd John , Lilge Lothar , Stone Jennifer
Published: March 2024

Purpose

Age and body mass index (BMI) are critical considerations when assessing individual breast cancer risk, particularly for women with dense breasts. However, age- and BMI-standardized estimates of breast density are not available for screen-aged women, and little is known about the distribution of breast density in women aged < 40. This cross-sectional study uses three different modalities: optical breast spectroscopy (OBS), dual-energy X-ray absorptiometry (DXA), and mammography, to describe the distributions of breast density across categories of age and BMI.

Methods

Breast density measures were estimated for 1,961 Australian women aged 18–97 years using OBS (%water and %water + %collagen). Of these, 935 women had DXA measures (percent and absolute fibroglandular dense volume, %FGV and FGV, respectively) and 354 had conventional mammographic measures (percent and absolute dense area). The distributions for each breast density measure were described across categories of age and BMI.

Results

The mean age was 38 years (standard deviation = 15). Median breast density measures decreased with age and BMI for all three modalities, except for DXA-FGV, which increased with BMI and decreased after age 30. The variation in breast density measures was largest for younger women and decreased with increasing age and BMI.

Conclusion

This unique study describes the distribution of breast density measures for women aged 18–97 using alternative and conventional modalities of measurement. While this study is the largest of its kind, larger sample sizes are needed to provide clinically useful age-standardized measures to identify women with high breast density for their age or BMI.
Morphological and Functional Correlations in Acute Central Serous Chorioretinopathy
Authors: Kiraly Peter , Šuštar Habjan Maja , Smrekar Jaka , Jaki Mekjavić Polona
Published: March 2024

Purpose

We evaluate morphological and functional correlations in patients with acute central serous chorioretinopathy (CSC).

Methods

A prospective study was conducted on 50 patients with an acute CSC episode lasting less than 3 months. At baseline, assessments included optical coherence tomography (OCT), best-corrected visual acuity (BCVA), contrast sensitivity (CS), microperimetry (MP), and multifocal electroretinography (mfERG). A correlation analysis between OCT morphological parameters (maximal subretinal fluid height (SRF), central retinal thickness (CRT), and macular volume (MV)) and functional parameters was conducted on the affected eye for each patient.

Results

Among the morphological parameters, SRF showed the strongest correlations with functional parameters (r absolute value range = 0.10–0.70). Weak correlations were observed between BCVA and morphological parameters (r absolute value range = 0.14–0.26). Average retinal sensitivity (MP-A) was the functional parameter displaying the most robust negative correlation with morphological parameters (r absolute value range = 0.61–0.70). In contrast, average contrast sensitivity (CS-A) and mfERG average amplitude density in the first (mfERG-A1) and second (mfERG-A2) ring showed weak to moderate (r absolute value range = 0.35–0.56) yet statistically significantly nonzero correlations.

Conclusions

SRF and CRT could serve as the most representative morphological proxies for visual function deficit in acute CSC patients. Retinal sensitivity, as measured by MP, may be superior to BCVA in clinical research studies or when an in-depth visual function evaluation is needed.
Interpretability of rectangle packing solutions with Monte Carlo tree search
Authors: Galán López Yeray , González García Cristian , García Díaz Vicente , Núñez Valdez Edward Rolando , Gómez Gómez Alberto
Published: March 2024

Packing problems have been studied for a long time and have great applications in real-world scenarios. In recent times, with problems in the industrial world increasing in size, exact algorithms are often not a viable option and faster approaches are needed. We study Monte Carlo tree search, a random sampling algorithm that has gained great importance in literature in the last few years. We propose three approaches based on MCTS and its integration with metaheuristic algorithms or deep learning models to obtain approximated solutions to packing problems that are also interpretable by means of MCTS exploration and from which knowledge can be extracted. We focus on two-dimensional rectangle packing problems in our experimentation and use several well known benchmarks from literature to compare our solutions with existing approaches and offer a view on the potential uses for knowledge extraction from our method. We manage to match the quality of state-of-the-art methods, with improvements in time with respect to some of them and greater interpretability.
A machine learning approach for diagnostic and prognostic predictions, key risk factors and interactions
Authors: Nasir Murtaza , Summerfield Nichalin S. , Carreiro Stephanie , Berlowitz Dan , Oztekin Asil
Published: March 2024

Machine learning (ML) has the potential to revolutionize healthcare, allowing healthcare providers to improve patient-care planning, resource planning and utilization. Furthermore, identifying key-risk-factors and interaction-effects can help service-providers and decision-makers to institute better policies and procedures. This study used COVID-19 electronic health record (EHR) data to predict five crucial outcomes: positive-test, ventilation, death, hospitalization days, and ICU days. Our models achieved high accuracy and precision, with AUC values of 91.6%, 99.1%, and 97.5% for the first three outcomes, and MAE of 0.752 and 0.257 days for the last two outcomes. We also identified interaction effects, such as high bicarbonate in arterial blood being associated with longer hospitalization in middle-aged patients. Our models are embedded in a prototype of an online decision support tool that can be used by healthcare providers to make more informed decisions.
Measurements of the Viscosity of Hydrogen and a (Hydrogen + Methane) Mixture with a Two-Capillary Viscometer
Authors: Betken Benjamin , Austegard Anders , Finotti Francesco , Caccamo Chiara , Stang Hans Georg Jacob , Khosravi Bahareh , Span Roland
Published: March 2024

Measurements of the viscosity of pure hydrogen and a binary (hydrogen + methane) mixture with a nominal composition 90 mol % hydrogen are presented. The measurements were conducted with a two-capillary viscometer relative to helium along three isotherms of (298.15, 323.15, and 348.15) K and at pressures of up to 18 MPa. Expanded relative combined uncertainties in viscosity range from (0.65 to 2.7) % (k = 2) for the hydrogen data, and from (0.91 to 3.2) % (k = 2) for the (hydrogen + methane) data. The viscosity data are compared to experimental literature data and viscosity correlations implemented in the NIST REFPROP v10.0 database. Good agreement between this work’s data, literature data, and the viscosity correlation was achieved for pure hydrogen. The (hydrogen + methane) mixture was compared to the Extended Corresponding States (ECS) model implemented in REFPROP v10.0. Relative deviations between the experimental data and the ECS model exceed the experimental uncertainty and were found to exhibit a positive trend with increasing density and a weakly pronounced negative trend with increasing temperature. No experimental literature data are available at overlapping state regions. Nonetheless, deviations to the ECS model imply reasonable consistency of this work’s data and literature data. In addition to experimental viscosities, experimental zero-density viscosity ratios of the fluids under investigation and helium are reported. Fairly good agreement within the experimental uncertainty of this work with a highly accurate literature value and a value obtained from accurate ab initio calculated data was achieved for hydrogen.
GnT-V-mediated aberrant N-glycosylation of TIMP-1 promotes diabetic retinopathy progression
Authors: Xi Xiaoting , Yang Yanni , Chen Qianbo , Ma Jia , Wang Xuewei , Deng Yachun , Wang Xi , Li Yan
Published: March 2024

Background

Vascular endothelial growth factor (VEGF) signaling pathway plays an important role in the progression of diabetic retinopathy (DR). The glycosylation modification process of many key functional proteins in DR patients is abnormal. However, the potential involvement of abnormal N-glycoproteins in DR progression remains unclear.

Methods

Glycoproteomic profiling of the vitreous humor was performed. The level of protein and N-glycoprotein was confirmed by Western blot and Lectin blot, respectively. The cell viability and migration efficiency were detected by CCK-8 and Transwell assay. Flow cytometry was conducted to analyze the level of cell apoptosis and reactive oxygen specie. Malondialdehyde, superoxide dismutase activity and VEGF content were detected by Enzyme linked immunosorbent assays. The interaction of metalloproteinase 1 (TIMP-1) with N-acetylglucosamine transferase V (GnT-V) was detected by GST pull-down. Hematoxylin and eosin staining and choroidal and retinal flat mount stained with fluorescein isothiocyanate-Dextran assay were used for functional research in vivo.

Results

We found that N-glycosylation was up-regulated in DR rats and high glucose (HG)-induced human retinal pigment epithelium cell line ARPE-19. HG-induced inhibited the viability of ARPE-19 cells and promoted cell apoptosis and oxidative stress (OS), but these effects were reversed with kifunensine treatment, GnT-V knockdown and TIMP-1 mutation. Additionally, GnT-V binds to TIMP-1 to promote N-glycosylation of TIMP-1. Over-expression of GnT-V inhibited the viability of ARPE-19 cells and promoted cell apoptosis, OS and VEGF release, which these effects were reversed with TIMP-1 mutation. Interestingly, over-expression of GnT-V promoted retinal microvascular endothelial cells (RMECs) angiogenesis but was revered with TIMP-1 mutation, which was terminally boosted by VEGF-A treatment. Finally, knockdown of GnT-V relieved DR progression.

Conclusion

The findings indicate that GnT-V can promote RMECs angiogenesis and ARPE-19 cells injury through activation VEGF signaling pathway by increasing TIMP-1 N-glycosylation level, which provides a new theoretical basis for the prevention of DR.
A Feature Selection Method Based on Feature-Label Correlation Information and Self-Adaptive MOPSO
Authors: Han Fei , Li Fanyu , Ling Qinghua , Han Henry , Lu Tianyi , Jiao Zijian , Zhang Haonan
Published: March 2024

Feature selection can be seen as a multi-objective task, where the goal is to select a subset of features that exhibit minimal correlation among themselves while maximizing their correlation with the target label. Multi-objective particle swarm optimization algorithm (MOPSO) has been extensively utilized for feature selection and has achieved good performance. However, most MOPSO-based feature selection methods are random and lack knowledge guidance in the initialization process, ignoring certain valuable prior information in the feature data, which may lead to the generated initial population being far from the true Pareto front (PF) and influence the population’s rate of convergence. Additionally, MOPSO has a propensity to become stuck in local optima during the later iterations. In this paper, a novel feature selection method (fMOPSO-FS) is proposed. Firstly, with the aim of improving the initial solution quality and fostering the interpretability of the selected features, a novel initialization strategy that incorporates prior information during the initialization process of the particle swarm is proposed. Furthermore, an adaptive hybrid mutation strategy is proposed to avoid the particle swarm from getting stuck in local optima and to further leverage prior information. The experimental results demonstrate the superior performance of the proposed algorithm compared to the comparison algorithms. It yields a superior feature subset on nine UCI benchmark datasets and six gene expression profile datasets.
CLSTM-SNP: Convolutional Neural Network to Enhance Spiking Neural P Systems for Named Entity Recognition Based on Long Short-Term Memory Network
Authors: Deng Qin , Chen Xiaoliang , Yang Zaiyan , Li Xianyong , Du Yajun
Published: March 2024

Membrane computing is a type of parallel computing system (generally called P system) abstracted from information exchange mechanisms in biological cells, tissues, or neurons, which can process data in a distributed and interpretable manner. LSTM-SNP, the first model of long short-term memory networks based on parameterized nonlinear Spiking neural P systems, was proposed recently. However, a systematic understanding and leveraging of the LSTM-SNP model to address named entity recognition (NER) and other natural language processing (NLP) tasks are still lacking. The bottleneck of the NER task lies in the scarcity of data and the vague definition of entity edges. Most approaches center on dataset handling, and there have been few attempts to address the issue in Spiking neural P (SNP) systems. This paper proposes a model named CLSTM-SNP based on the LSTM-SNP, aiming to tackle the NER problem in the field of SNP systems for the first time. First, this study employs a CNN layer to obtain character-level characteristics. Second, GloVe word vectors are utilized as word representations. Third, the research employs the LSTM-SNP to analyze textual features. We subsequently studied CLSTM-SNP’s effectiveness in addressing NER problems on CoNLL-2003 and OntoNotes 5.0 datasets and compared it to the results of five other baseline methods. Our model CLSTM-SNP achieved a macro F1-score of 89.2 $$\%$$
%
on CoNLL-2003 and 75.5$$\%$$
%
on OntoNotes 5.0, respectively. The performance of CLSTM-SNP and LSTM-SNP indicates a great potential for handling named entity recognition or other sequential tasks in NLP.
Soil Contamination and Biomarkers in Ucides cordatus in Mangroves from Baía de Todos os Santos, Bahia, Brazil
Authors: Ramos M. A. V. , da Rocha S. S. , Winkaler E. U. , Nobrega G. N. , da Cruz Carvalho J. , de Souza Santos A. Zaga , Otero X. L.
Published: March 2024

The aim of the present study was to analyze the response to exposure to pollutants (trace elements and organic pollutants) using biomarkers (micronucleated cells and glutathione S-transferase and catalase activity) in uçá crab Ucides cordatus. The study was carried out at four sites: Cacha Prego (CP) and Ponta Grossa (PG), areas with low anthropic activity; and Ilha de Maré (IM) and Pitinga (PT), areas affected by industrial activity. At each site, soil and crab samples were collected to analyze the contents of potentially toxic elements (total concentration and chemical partitioning of trace elements), polycyclic aromatic hydrocarbons (PAHs), and polychlorinated biphenyls (PCBs). Both total concentrations and geochemical fractions of Cu, Zn, and Ni in soils were significantly higher in IM. Likewise, higher reactive Pb contents were observed in mangroves both in IM and in PG. Values above quality limits were observed for organic pollutants (PAHs) in soils from CP and PT, while PCB contents were below the maximum permissible levels. Metals in crabs also showed spatial variations, with higher Cu concentrations in all tissues in IM and PT and higher Ni concentrations in hepatopancreas in PT during the dry season. PAH values in crabs did not show spatial variations; however, crustaceans with contents above maximum limits in their muscle tissue were found in CP. Crabs from the Baia de Todos Santos showed different responses in biomarker expression, with higher enzymatic activity and greater numbers of micronucleated cells in crabs from IM, suggesting oxidative stress and genotoxicity in this mangrove forest.
Hybrid Molecular and Functional Micro-CT Imaging Reveals Increased Myocardial Apoptosis Preceding Cardiac Failure in Progeroid Ercc1 Mice
Authors: van Thiel Bibi S. , de Boer Martine , Ridwan Yanto , de Kleijnen Marion G. J. , van Vliet Nicole , van der Linden Janette , de Beer Isa , van Heijningen Paula M. , Vermeij Wilbert P. , Hoeijmakers Jan H. J. , Danser A. H. Jan , Kanaar Roland , Duncker Dirk J. , van der Pluijm Ingrid , Essers Jeroen
Published: March 2024

Purpose

In this study, we explored the role of apoptosis as a potential biomarker for cardiac failure using functional micro-CT and fluorescence molecular tomography (FMT) imaging techniques in Ercc1 mutant mice. Ercc1 is involved in multiple DNA repair pathways, and its mutations contribute to accelerated aging phenotypes in both humans and mice, due to the accumulation of DNA lesions that impair vital DNA functions. We previously found that systemic mutations and cardiomyocyte-restricted deletion of Ercc1 in mice results in left ventricular (LV) dysfunction at older age.

Procedures and Results

Here we report that combined functional micro-CT and FMT imaging allowed us to detect apoptosis in systemic Ercc1 mutant mice prior to the development of overt LV dysfunction, suggesting its potential as an early indicator and contributing factor of cardiac impairment. The detection of apoptosis in vivo was feasible as early as 12 weeks of age, even when global LV function appeared normal, underscoring the potential of apoptosis as an early predictor of LV dysfunction, which subsequently manifested at 24 weeks.

Conclusions

This study highlights the utility of combined functional micro-CT and FMT imaging in assessing cardiac function and detecting apoptosis, providing valuable insights into the potential of apoptosis as an early biomarker for cardiac failure.
Differences in Psychological Health and Weight Loss after Bariatric Metabolic Surgery between Patients with and without Pain Syndromes
Authors: Pyykkö Johanna E. , Zwartjes Max , Nieuwdorp Max , van Olst Nienke , Bruin Sjoerd C. , van de Laar Arnold W. , Sanderman Robbert , Hagedoorn Mariët , Gerdes Victor E. A.
Published: March 2024

Purpose

Chronic pain and obesity often co-occur, negatively affecting one another and psychological wellbeing. Pain and psychological wellbeing improve after bariatric metabolic surgery (BMS), however, it is unknown whether psychological wellbeing improves differently after weight loss between patients with and without chronic pain. We investigated whether weight loss is associated with greater psychological wellbeing and functioning change after BMS, comparing patients with and without preoperative pain syndromes.

Methods

Depression, health-related quality of life, self-esteem, self-efficacy to exercise and controlling eating behaviours, physical activity, and food cravings were measured before and 24 months after BMS among 276 patients with obesity. The presence of preoperative chronic pain syndromes was examined as a moderator for the relationship between 24-month weight loss and changes in psychological outcomes.

Results

Chronic pain syndromes were present among 46% of patients. Weight loss was associated with greater improvement in health-related quality of life, self-efficacy to exercise and controlling eating behaviours, self-esteem and greater amelioration in food cravings. Pain syndromes only moderated negatively the relationship between the postoperative weight loss and change in self-efficacy to control eating behaviours (b = -0.49, CI [-0.88,-0.12]).

Conclusion

Patients with and without chronic pain showed similar improvements in weight and psychological wellbeing and behaviours after BMS. The relationship between weight loss and the improvement of self-efficacy to control eating behaviours was weaker among patients with chronic pain syndrome. Further work, measuring pain severity over time, is needed to shed light on the mechanism underlying pain and postoperative change in psychological wellbeing and weight loss.

Graphical Abstract
CIT Training Among Law Enforcement: Does It Work?
Authors: Boddy Kierstyn , Athaide-Victor Elizabeth , Law Fang-Mei , Sharp Johnathon
Published: March 2024

The relationship between law enforcement and those with mental illness is severely strained and possibly even broken. But who caused this rift in the relationship? Is law enforcement to blame? Are those with a mental illness to blame? Or, does the issue stem from a bigger problem of deinstitutionalization and negative stigmas that society has against both mentioned populations? The purpose of this study was to dive deeper into the relationship between law enforcement officers and those with mental illness to seek the root cause of the disconnect, as well as what can be done to bridge the gap. Previous research has focused on the law enforcement perspective, focusing on what training (if any) they have for dealing with citizens with mental illnesses as well as how those in law enforcement perceive people with mental illnesses while on the job. These perceptions are yet another possible explanation of the disconnect and could potentially be part of the solution to help mend the break between law enforcement and those suffering from a mental illness. The present study sought to examine the effects that CIT training has on the response outcomes when law enforcement officers respond to those with mental illness. These response outcomes, when ranked by severity, can help to explain the importance of CIT training and its effectiveness, especially when compared to the previous studies data pool of officer perspectives. The results of this study are compelling and create an effortless opening for conversation on a topic that is difficult for many to talk about.
Pilot Evaluation of the POWER Program: Positive Outcomes with Emotion Regulation
Authors: Zakszeski Brittany , Cain Michelle , Eklund Katie , Heurich Lissy , Friedman Reagan , Ward Ashleigh , Zhou Jingwen
Published: March 2024

The Positive Outcomes With Emotion Regulation (POWER) Program is a transdiagnostic intervention for adolescents at risk of developing emotional disorders. The POWER Program was designed to be implemented in secondary schools, by school personnel with or without specialized mental health training, as a Tier 2 intervention. In this pilot study, the POWER Program was implemented by school psychologists and school psychologists-in-training and evaluated across four focal student participants using a multiple-baseline-across-participants single-case design. Program efficacy was assessed using systematic direct classroom observations of student negative affect and social engagement as well as student and caregiver ratings of emotional and behavioral symptoms. Program usability was assessed through rating scales completed by intervention facilitators and student participants. Overall, results provide evidence of the POWER Program’s small- to large-sized effects on students’ emotional and behavioral functioning as observed in the classroom and self-reported by students. In addition, results suggest implementation facilitators’ and students’ positive impressions of the program, evident in ratings of high understanding, feasibility, and acceptability across groups. Study limitations are highlighted with attention to opportunities to further refine and evaluate the POWER Program.
Gap Junctions May Have A Computational Function In The Cerebellum: A Hypothesis
Authors: Gilbert Mike , Rasmussen Anders
Published: March 2024

In the cerebellum, granule cells make parallel fibre contact on (and excite) Golgi cells and Golgi cells inhibit granule cells, forming an open feedback loop. Parallel fibres excite Golgi cells synaptically, each making a single contact. Golgi cells inhibit granule cells in a structure called a glomerulus almost exclusively by GABA spillover acting through extrasynaptic GABAA receptors. Golgi cells are connected dendritically by gap junctions. It has long been suspected that feedback contributes to homeostatic regulation of parallel fibre signals activity, causing the fraction of the population that are active to be maintained at a low level. We present a detailed neurophysiological and computationally-rendered model of functionally grouped Golgi cells which can infer the density of parallel fibre signals activity and convert it into proportional modulation of inhibition of granule cells. The conversion is unlearned and not actively computed; rather, output is simply the computational effect of cell morphology and network architecture. Unexpectedly, the conversion becomes more precise at low density, suggesting that self-regulation is attracted to sparse code, because it is stable. A computational function of gap junctions may not be confined to the cerebellum.
Effects of Baclofen on Central Paroxysmal Positional Downbeat Nystagmus
Authors: Yun So-Yeon , Lee Jong-Hee , Kim Hyo-Jung , Choi Jeong‑Yoon , Kim Ji-Soo
Published: March 2024

Paroxysmal positional nystagmus frequently occurs in lesions involving the cerebellum, and has been ascribed to disinhibition and enhanced canal signals during positioning due to cerebellar dysfunction. This study aims to elucidate the mechanism of central positional nystagmus (CPN) by determining the effects of baclofen on the intensity of paroxysmal positional downbeat nystagmus due to central lesions. Fifteen patients with paroxysmal downbeat CPN were subjected to manual straight head-hanging before administration of baclofen, while taking baclofen 30 mg per day for at least one week, and two weeks after discontinuation of baclofen. The maximum slow phase velocity (SPV) and time constant (TC) of the induced paroxysmal downbeat CPN were analyzed. The positional vertigo was evaluated using an 11-point numerical rating scale (0 to 10) in 9 patients. After treatment with baclofen, the median of the maximum SPV of paroxysmal downbeat CPN decreased from 30.1°/s [interquartile range (IQR) = 19.6—39.0°/s] to 15.2°/s (IQR = 11.2—22.0°/s, Wilcoxon signed rank test, p < 0.001) with the median decrement ratio at 40.2% (IQR = 28.2—50.6%). After discontinuation of baclofen, the maximum SPV re-increased to 24.6°/s (IQR = 13.1—34.4°/s, Wilcoxon signed rank test, p = 0.001) with the median increment ratio at 23.5% (IQR = 5.2—87.9%). In contrast, the TCs of paroxysmal downbeat CPN remained unchanged at approximately 3.0 s throughout the evaluation. The positional vertigo also decreased with the medication (Wilcoxon signed rank test, p = 0.020), and remained unchanged even after discontinuation of medication (Wilcoxon signed rank test, p = 0.737). The results of this study support the prior presumption that paroxysmal CPN is caused by enhanced responses of the semicircular canals during positioning due to cerebellar disinhibition. Baclofen may be tried in symptomatic patients with paroxysmal CPN.
Torn Between Love and Hate: Mouse Tracking Ambivalent Attitudes Towards Robots
Authors: Stapels Julia G. , Eyssel Friederike
Published: March 2024

Robots are a source of evaluative conflict and thus elicit ambivalence. In fact, psychological research has shown across domains that people simultaneously report strong positive and strong negative evaluations about one and the same attitude object. This is defined as ambivalence. In the current research, we extended existing ambivalence research by measuring ambivalence towards various robot-related stimuli using explicit (i.e., self-report) and implicit measures. Concretely, we used a mouse tracking approach to gain insights into the experience and resolution of evaluative conflict elicited by robots. We conducted an extended replication across four experiments withN= 411 overall. This featured a mixed-methods approach and included a single paper meta-analysis. Thereby, we showed that the amount of reported conflicting thoughts and feelings (i.e., objective ambivalence) and self-reported experienced conflict (i.e., subjective ambivalence) were consistently higher towards robot-related stimuli compared to stimuli evoking univalent responses. Further, implicit measures of ambivalence revealed that response times were higher when evaluating robot-related stimuli compared to univalent stimuli, however results concerning behavioral indicators of ambivalence in mouse trajectories were inconsistent. This might indicate that behavioral indicators of ambivalence apparently depend on the respective robot-related stimulus. We could not obtain evidence of systematic information processing as a cognitive indicator of ambivalence, however, qualitative data suggested that participants might focus on especially strong arguments to compensate their experienced conflict. Furthermore, interindividual differences did not seem to substantially influence ambivalence towards robots. Taken together, the current work successfully applied the implicit and explicit measurement of ambivalent attitudes to the domain of social robotics, while at the same time identifying potential boundaries for its application.