bluuebunny/crossref_metadata_2025_split huggingface dataset:
The influence of the gingival phenotype on implant survival rate and clinical parameters: a systematic review
Authors: da Silva Diego Marques , Castro Filipe , Martins Bruno , Fraile Javier Flores , Fernandes Juliana Campos Hasse , Fernandes Gustavo Vicentis Oliveira 
Published: February 2025

Abstract

Objective
The goal of this systematic review was to verify whether the gingival phenotype (thick or thin) could impact the dental implant survival rate by affecting the marginal bone.

Methods
The search was carried out on PubMed/MedLine, PubMed Central, and B-On databases. The research question was: “Does gingival phenotype positively or negatively influence marginal bone loss around dental implants?” The inclusion criteria were: any clinical trial/study, comparative study, prospective or retrospective articles, systematic review that addressed at least a 1-year follow-up with an assessment of the marginal bone loss (MBL) around dental implants, articles that reported the gingival phenotype (thin or thick) and were published in the last 13 years. The exclusion criteria were narrative or other reviews, letters to the editor, and commentaries. Data extraction included the author’s name, year of publication, type of study, sample size, number of implants, method used, and outcomes presented. The extracted data was summarized and presented in the results section. Critical Appraisal tool in JBI Systematic Reviews was used to determine the possibility of bias.

Results
A total of 62 articles were found, but eight articles were relevant to compose this study. After deep evaluation, it was possible to observe the implant success rate for both gingival phenotypes, thin and thick, was greater than 91% within a follow-up of up to 5 years. Therefore, it is unclear whether the thickness of the gingival tissue surrounding the implant can directly influence the marginal bone level. The gingival phenotype may be indirectly involved in the survival rate of dental implants, as it can be a risk factor for peri-implantitis, leading to marginal bone loss beyond what is expected.

Discussion
The thin gingival phenotype is one of the main risk factors for additional bone loss. It is crucial to know how to preserve the healthy condition.

Conclusion
Within the results found, the gingival phenotype is indirectly related to implant survival rate and clinical parameters, which were respectively high and non-conclusive. Therefore, a higher risk of peri-implantitis is suggested when a thin phenotype is present.
Deep empirical neural network for optical phase retrieval over a scattering medium
Authors: Tu Huaisheng , Liu Haotian , Pan Tuqiang , Xie Wuping , Ma Zihao , Zhang Fan , Xu Pengbai , Wu Leiming , Xu Ou , Xu Yi , Qin Yuwen 
Published: February 2025

Abstract
Supervised learning, a popular tool in modern science and technology, thrives on huge amounts of labeled data. Physics-enhanced deep neural networks offer an effective solution to alleviate the data burden by incorporating an analytical model that interprets the underlying physical processes. However, it completely fails in tackling systems without analytical solution, where wave scattering systems with multiple input multiple output are typical examples. Herein, we propose a concept of deep empirical neural network (DENN) that is a hybridization of a deep neural network and an empirical model, which enables seeing through an opaque scattering medium in an untrained manner. The DENN does not rely on labeled data, all while delivering as high as 58% improvement in fidelity compared with the supervised learning using 30000 data pairs for achieving the same goal of optical phase retrieval. The DENN might shed new light on the applications of deep learning in physics, information science, biology, chemistry and beyond.
Identifying neurobiological heterogeneity in clinical high-risk psychosis: a data-driven biotyping approach using resting-state functional connectivity
Authors: Tang Xiaochen , Wei Yanyan , Pang Jiaoyan , Xu Lihua , Cui Huiru , Liu Xu , Hu Yegang , Ju Mingliang , Tang Yingying , Long Bin , Liu Wei , Su Min , Zhang Tianhong , Wang Jijun 
Published: February 2025

Abstract
To explore the neurobiological heterogeneity within the Clinical High-Risk (CHR) for psychosis population, this study aimed to identify and characterize distinct neurobiological biotypes within CHR using features from resting-state functional networks. A total of 239 participants from the Shanghai At Risk for Psychosis (SHARP) program were enrolled, consisting of 151 CHR individuals and 88 matched healthy controls (HCs). Functional connectivity (FC) features that were correlated with symptom severity were subjected to the single-cell interpretation through multikernel learning (SIMLR) algorithm in order to identify latent homogeneous subgroups. The cognitive function, clinical symptoms, FC patterns, and correlation with neurotransmitter systems of biotype profiles were compared. Three distinct CHR biotypes were identified based on 646 significant ROI-ROI connectivity features, comprising 29.8%, 19.2%, and 51.0% of the CHR sample, respectively. Despite the absence of overall FC differences between CHR and HC groups, each CHR biotype demonstrated unique FC abnormalities. Biotype 1 displayed augmented somatomotor connection, Biotype 2 shown compromised working memory with heightened subcortical and network-specific connectivity, and Biotype 3, characterized by significant negative symptoms, revealed extensive connectivity reductions along with increased limbic-subcortical connectivity. The neurotransmitter correlates differed across biotypes. Biotype 2 revealed an inverse trend to Biotype 3, as increased neurotransmitter concentrations improved functional connectivity in Biotype 2 but reduced it in Biotype 3. The identification of CHR biotypes provides compelling evidence for the early manifestation of heterogeneity within the psychosis spectrum, suggesting that distinct pathophysiological mechanisms may underlie these subgroups.
Limited impact of Salmonella stress and persisters on antibiotic clearance
Authors: Fanous Joseph , Claudi Beatrice , Tripathi Vishwachi , Li Jiagui , Goormaghtigh Frédéric , Bumann Dirk 
Published: February 2025

Abstract
Antimicrobial compounds are essential for controlling bacterial infections. Stress-induced bacterial tolerance and persisters can undermine antimicrobial activities under laboratory conditions, but their quantitative effects under physiological conditions remain unclear1,2. Here we determined constraints on clearance of Salmonella by antimicrobials in infected mice and tissue-mimicking chemostats. The antibiotics enrofloxacin and ceftriaxone exhibited poor anti-Salmonella activity under both conditions, primarily owing to severe nutrient starvation, which restricted Salmonella replication3–5. Other infection-associated conditions, such as acidic pH, glucose, oxidative stress, nitrosative stress, antimicrobial peptides, osmolarity, oxygen limitation, carbon dioxide and carbonate, as well as drug efflux, toxin–antitoxin modules and cell size had limited effects. A subset of resilient Salmonella appeared as a key obstacle for clearance by enrofloxacin, based on the biphasic decline of Salmonella colony-forming units. However, these data were misleading, because colony formation was confounded by extensive post-exposure killing. More accurate single-cell, real-time assays showed uniformly slow damage, indicating high resilience across the entire Salmonella population. The resulting extensive survival of bulk bacteria minimized the effect of hyper-resilient persisters. Thus, starvation-induced general resilience of Salmonella was the main cause of poor antibiotic clearance. These findings highlight the importance of quantifying antibiotic activity with real-time, single-cell assays under physiological conditions.
Daratumumab plus bortezomib, lenalidomide and dexamethasone for transplant-ineligible or transplant-deferred newly diagnosed multiple myeloma: the randomized phase 3 CEPHEUS trial
Authors: Usmani Saad Z. , Facon Thierry , Hungria Vania , Bahlis Nizar J. , Venner Christopher P. , Braunstein Marc , Pour Ludek , Martí Josep M. , Basu Supratik , Cohen Yael C. , Matsumoto Morio , Suzuki Kenshi , Hulin Cyrille , Grosicki Sebastian , Legiec Wojciech , Beksac Meral , Maiolino Angelo , Takamatsu Hiroyuki , Perrot Aurore , Turgut Mehmet , Ahmadi Tahamtan , Liu Weiping , Wang Jianping , Chastain Katherine , Vermeulen Jessica , Krevvata Maria , Lopez-Masi Lorena , Carey Jodi , Rowe Melissa , Carson Robin , Zweegman Sonja 
Published: February 2025

Abstract
Frontline daratumumab-based triplet and quadruplet standard-of-care regimens have demonstrated improved survival outcomes in newly diagnosed multiple myeloma (NDMM). For patients with transplant-ineligible NDMM, triplet therapy with either daratumumab plus lenalidomide and dexamethasone (D-Rd) or bortezomib, lenalidomide and dexamethasone (VRd) is the current standard of care. This phase 3 trial evaluated subcutaneous daratumumab plus VRd (D-VRd) in patients with transplant-ineligible NDMM or for whom transplant was not planned as the initial therapy (transplant deferred). Some 395 patients with transplant-ineligible or transplant-deferred NDMM were randomly assigned to eight cycles of D-VRd or VRd followed by D-Rd or Rd until progression. The primary endpoint was overall minimal residual disease (MRD)-negativity rate at 10−
5 by next-generation sequencing. Major secondary endpoints included complete response (CR) or better (≥CR) rate, progression-free survival and sustained MRD-negativity rate at 10−
5. At a median follow-up of 58.7 months, the MRD-negativity rate was 60.9% with D-VRd versus 39.4% with VRd (odds ratio, 2.37; 95% confidence interval (CI), 1.58–3.55; P < 0.0001). Rates of ≥CR (81.2% versus 61.6%; P < 0.0001) and sustained MRD negativity (≥12 months; 48.7% versus 26.3%; P < 0.0001) were significantly higher with D-VRd versus VRd. Risk of progression or death was 43% lower for D-VRd versus VRd (hazard ratio, 0.57; 95% CI, 0.41–0.79; P = 0.0005). Adverse events were consistent with the known safety profiles for daratumumab and VRd. Combining daratumumab with VRd produced deeper and more durable MRD responses versus VRd alone. The present study supports D-VRd quadruplet therapy as a new standard of care for transplant-ineligible or transplant-deferred NDMM. ClinicalTrials.gov registration: NCT03652064.
Efficacy of bacteriophages with Aloe vera extract in formulated cosmetics to combat multidrug-resistant bacteria in skin diseases
Authors: Maan Sodaf A. , Faiesal Abeer A. , Gamar Gamar M. , El Dougdoug Noha K. 
Published: February 2025

Abstract
Phage therapy offers a promising alternative to antibiotic treatment for combating illnesses caused by multidrug-resistant bacteria. In this study, pathogenic bacteria Staphylococcus aureus and Pseudomonas aeruginosa were isolated from pus and skin infected fluidsusing selective media. These bacterial isolates were biochemically identified as S. aureus and P. aeruginosa with probabilities of 98% and 99%, respectively, through VITEK2 system, and were confirmed as multidrug-resistant based on minimum inhibitory concentration test using colorimetric reagent cards. Lytic phages specific to these isolates were isolated, identified through plaque assays, transmission electron microscopy and classified morphologically according to the new International Committee on Taxonomy of Viruses classification as members of the Straboviridae, Drexlerviridae, and Autographiviridae families. A cosmetic gel formulation combining Aloe vera extract and the phage cocktail was prepared and tested. This gel significantly enhanced phage longevity and reduced bacterial growth by 95.5% compared to the reductions of 90.5% with Aloe Vera extract alone and 45.7% with the basic cosmetic gel. The phage remained effective for 4 to over 12 weeks after being preserved in the cosmetic formula, maintaining populations ranging from 5 × 103 to 25 × 104 PFU/mL in vitro. These findings highlight the potential of phage-based formulations, such as Vena Skin Gel, as innovative biotherapeutic tools for managing skin infections.
Impact of host physiology and external stressors on the bacterial community of Schmidtea mediterranea
Authors: Bijnens Karolien , Thijs Sofie , Alfano Rossella , McAmmond Breanne , Van Hamme Jonathan , Artois Tom , Plusquin Michelle , Vangronsveld Jaco , Smeets Karen 
Published: February 2025

Abstract
To fully comprehend host-microorganism interactions, it is crucial to understand the composition and diversity of the microbiome, as well as the factors that shape these characteristics. We investigated microbiome variation using the freshwater planarian Schmidtea mediterranea, an invertebrate model in regeneration biology and (eco-)toxicology, by exposing the organisms to various controlled conditions. The microbiome composition exhibited high variability, with most of the bacteria belonging to the Betaproteobacteria. Among the diverse microbial communities, a few genera, such as Curvibacter, were consistently present, but exhibited significant alterations in response to changing conditions. The relative abundance of Curvibacter fluctuated during the regeneration process, initially increasing before returning to a composition similar to the beginning situation. After applying external stress, the relative abundance of Curvibacter and other genera decreased. Variation over time, between different origin laboratories and between individuals, showed that additional, yet to-be-identified, factors of variation are present. Taking all results together, our study provides a solid basis for future research focusing on bacterial functionality in planarians and other invertebrates.
An unconstrained four pool model analysis of proton relaxation and magnetization transfer in ex vivo white matter
Authors: Wallstein Niklas , Pampel André , Müller Roland , Jäger Carsten , Morawski Markus , Möller Harald E. 
Published: February 2025

Abstract
Understanding proton relaxation in the brain’s white matter remains an active field of magnetic resonance imaging research. Models of varying complexity have been proposed to link measurements to tissue composition/microstructure, in particular myelination. Although the presence of multiple aqueous and nonaqueous proton pools is well established experimentally, so-called “quantitative MRI” is usually based on simpler models due to the large number of model parameters. In this work, a comprehensive set of parameters characterizing a four-pool model is obtained. A piece of fixed porcine spinal-cord WM was investigated at 3 T and temperatures between 21 and 35 °C. Measurements included a wide range of preparations of the spin system in combination with long echo trains to achieve sensitivity to all model parameters. The results allow the extraction of all intrinsic relaxation and exchange rates as well as assigning them to specific dynamic processes involving tissue water. A critical assessment indicates that simpler models often lack specificity to myelin.
Cortical and subcortical activities during food rewards versus social interaction in rats
Authors: Rocha-Almeida Florbela , Conde-Moro Ana R. , Fernández-Ruiz Antonio , Delgado-García José M. , Gruart Agnès 
Published: February 2025

Abstract
Balancing food foraging with social interaction is crucial for survival and reproduction in many species of mammals. We wanted to investigate the reward preferences in adult male rats by allowing them to lever-press for both food and social rewards (interaction with another rat), while their performance and electrophysiological activities were recorded. Local field potentials (LFPs) were analyzed across five neuroanatomical regions involved in reward processing, decision-making, and social behavior. Despite ad libitum food availability, rats consistently prioritized food. LFP analysis revealed a decrease in nucleus accumbens (NAc) spectral power following social interaction, accompanied by specific alterations in delta and theta bands within the medial prefrontal cortex (mPFC). The spectral power of LFPs delta and/or theta bands were different for the five selected regions following food reward vs. social interactions. Cross-frequency coupling analysis provided further insights, demonstrating dynamic changes in theta-to-gamma coupling during both food and social rewards, with distinct roles for slow- and fast-gamma frequencies. These findings shed light on the intricate neural processes underlying reward preferences and/or decision-making choices, highlighting the NAc’s potential role in social reward processing, and the mPFC’s involvement in modulating theta–gamma rhythms during reward-related decision-making.
Analysis of quality of life and periodontal health with an eight-unit maxillary fixed retainer through a prospective clinical trial
Authors: Abbas Mohamed H. , Abdalla Essam M. , El Harouni Nadia M. , Marzouk Eiman S. 
Published: February 2025

Abstract
Retention is crucial in orthodontics, aiming to preserve treatment outcomes and enhance patient satisfaction with permanent fixed retainers. However, a removable retainer may be needed with fixed retainers to prevent unwanted changes. An eight-unit extended fixed retainer is proposed to eliminate the need for a removable retainer, addressing the undesired changes associated with six-unit fixed retainers. The impact of extended retainers on periodontium and quality of life remains unexplored. This study evaluates the periodontal response and patient-reported quality of life with an eight-unit maxillary fixed retainer. A single-arm prospective clinical trial with only twenty-eight test group patients (6 males, 22 females) who finished active orthodontic treatment were recruited. The mean age was (19.8 ± 4.5 years). This research was approved by the institutional review board of the Faculty of Dentistry, Alexandria University (IORG:0008839, No-0479-8/2022). The registration date of this study was (5/06/2023). An eight-unit maxillary fixed retainer was bonded to the palatal surface of the maxillary incisors, canines, and first or second premolars directly after debonding the brackets. The periodontal assessment and quality of life were carried out through clinical examination and valid questionnaires and the patients were followed up for 12 months. The periodontal response improved significantly at 1-year follow-up. The Probing depth, Gingival index, Plaque index, Bleeding index, and mobility index were significantly lower in these patients. Quality of life was assessed by the OHIP-14. The mean score decreased by -1.86 (SD = 4.19), and the acceptance of the orthodontic appliance scale score increased by 0.68 (SD = 0.86), which was significant with a p-value < 0.001. For 12 months of follow-up, an eight-unit maxillary retainer did not adversely affect the periodontal ligaments. meets patients’ expectations and maintains a high quality of life.
Advanced bio-hybrid drone for superior odor-source localization: high-precision and extended-range detection capabilities
Authors: Fukui Chihiro , Uchida Tomoya , Koizumi Sakito , Murayama Yuta , Liu Hao , Nakata Toshiyuki , Terutsuki Daigo 
Published: February 2025

Abstract
Bio-hybrid drones, which combine biological odor sensors with small drones, introduce an innovative navigation method that compensates for traditional image-based navigation, enhancing the capabilities of aerial robots. Inspired by the odor-source search behavior observed in biological organisms, we identified two key elements for improving odor source direction estimation accuracy for bio-hybrid drones: (1) increasing the anisotropy of the odor sensor using a sensor enclosure, and (2) implementing a stepped rotation algorithm that strategically incorporates pauses during scanning. This integration resulted in a doubling of both search accuracy and range, achieving a search distance of up to 5 m, significantly exceeding the performance of a previous algorithm that sequentially combined rotational and linear motions. Although these elements are commonly observed in various arthropods, they are underapplied in robotics applications. This study provides a novel perspective to robotic olfactory navigation techniques by leveraging these biological behaviors to enhance robotic functionality.
Parameter efficient face frontalization in image sequences via GAN inversion
Authors: Ahmadi Mohammadhossein , Kambarani Nima , Mohammadi Mohammad Reza 
Published: February 2025

AbstractProcessing facial images with varying poses is a significant challenge. Most existing face frontalization methods rely on heavy architectures that struggle with small datasets and produce low‐quality images. Additionally, although video frames provide richer information, these methods typically use single images due to the lack of suitable multi‐image datasets. To address these issues, a parameter‐efficient framework for high‐quality face frontalization in both single and multi‐frame scenarios is proposed. First, a high‐quality, diverse dataset is created for single and multi‐image face frontalization tasks. Second, a novel single‐image face frontalization method is introduced by combining GAN inversion with transfer learning. This approach reduces the number of trainable parameters by over 91% compared to existing GAN inversion methods while achieving far more photorealistic results than GAN‐based methods. Finally, this method is extended to sequences of images, using attention mechanisms to merge information from multiple frames. This multi‐frame approach reduces artefacts like eye blinks and improves reconstruction quality. Experiments demonstrate that this single‐image method outperforms pSp, a state‐of‐the‐art GAN inversion method, with a 0.15 LPIPS improvement and a 0.10 increase in ID similarity. This multi‐frame approach further improves identity preservation to 0.87, showcasing its effectiveness for high‐quality frontal‐view reconstructions.
DDPGAT: Integrating MADDPG and GAT for optimized urban traffic light control
Authors: Azad‐Manjiri Meisam , Afsharchi Mohsen , Abdoos Monireh 
Published: February 2025

AbstractUrban traffic control is a complex and dynamic multi‐agent challenge, characterized by the need for efficient coordination and real‐time responsiveness in fluctuating traffic conditions. Traditional methods often fall short in adapting to these dynamic environments. This article introduces “DDPGAT”, a novel framework that merges Multi‐Agent Deep Deterministic Policy Gradients (MADDPG) with Graph Attention Networks (GATs) for optimized urban traffic control, further enhanced by a unique moral reward component. DDPGAT empowers traffic signal controllers as independent agents using GATs for dynamic road importance assessment. Shared attention scores during training enhance each agent's understanding of local and wider traffic patterns, essential for developing adaptive control policies. A key innovation in DDPGAT is the moral reward function, encouraging decisions that consider neighboring intersections' traffic, thus promoting ethical traffic management. The experiments demonstrate that DDPGAT significantly boosts traffic throughput and reduces congestion, confirming its effectiveness in diverse traffic conditions. The integration of MADDPG, GATs, and a moral reward strategy in DDPGAT presents a sophisticated, robust approach for managing the complexities of urban traffic control, marking a notable progression in intelligent traffic system technologies.