bluuebunny/crossref_metadata_2025 huggingface dataset:
A Possible Method of Using Astronomical Observations to Probe Quantum Kinematic Properties of Gravity
Authors: Zhao Dongcheng
Published: May 2024

The Newtonian gravity considers gravity is a force that action at a distance, however, if gravity is quantized, then it should not be an instantaneous force, but propagates toward a direction at the speed of light by gravitational quanta. The quantum kinematic gravitational equation is a possible new way to describe gravity which established based on Newton’s gravitational equation and quantum theory. Here is a possible method of using quantum kinematic gravitational equation to describe the anomalous acceleration of 1I/2017 U1 'Oumuamua, the margin of error between the result calculated by the equation and the astronomical observation during Oct 19, 2017 - May 3, 2018 is approximately 8% − 10%. There should be an angle difference in the tangential direction of approximate 28 arcseconds between its trajectories calculated respectively by quantum kinematic gravitational equation and by the Newton’s gravitational equation, during Oumuamua's whole journey in the Solar system. The accumulation of extra velocity caused by quantum kinematic gravitational force may provide extra kinetic energy, which may be one of the reasons the Moon orbital expansion.
Beneficial redox activity of halide solid electrolytes empowering high-performance anodes in all-solid-state batteries
Authors: Wagemaker Marnix , Cheng Zhu , Zhao Wenxuan , Wang Qidi , Zhao Chenglong , Lavrinenko Anastasia K. , Vasileiadis Alexandros , Landgraf Victor , Bannenberg Lars , Ganapathy Swapna
Published: May 2024

All-solid-state batteries receive ample attention having the potential to outperform Li-ion batteries in safety characteristics and energy density. The latter holds true if they are compatible with next-generation high-capacity anodes. However, most highly ion-conductive solid electrolytes decompose at the low operating potentials of next-generation anodes, leading to irreversible lithium loss and increased cell resistances. Here we introduce the concept of the dynamic stability of solid electrolytes, and demonstrate how this phenomenon can be utilized to improve all-solid-state battery performance. Halide electrolytes such as Li3YCl3Br3 and Li2ZrCl6, considered unstable at low working potentials, are shown to exhibit a structurally reversible redox activity beyond their electrochemical stability windows. Low potentials result in reversible lithiation of these halide solid electrolytes, introducing three advantages to the benefit of all-solid-state battery performance. First, the dynamic stability window is wider than their electrochemical stability window, thereby increasing their compatibility with anodes. Second, the lithiation of these halides increases their ionic conductivity rather than compromising it. Finally, the solid electrolyte contributes to the reversible capacity of the all-solid-state battery. The benefit of this dynamic stability window is demonstrated through halide-based cost-effective red phosphorus anodes that fall within this window, resulting in high reversible capacities (2308 mAh g− 1), high rate capacity retention (1024 mAh g− 1 at 7.75 mA cm− 2) and an extended cycle life (61% retention after 1780 cycles). Furthermore, high areal capacity (7.65 mAh cm− 2) and stability (70% retention after 1000 cycles) are achieved for exclusive halide-based full cells with uncoated high-voltage cathodes in combination with red phosphorous anodes. The beneficial redox activity of halide electrolytes that is unveiled, opens up novel application scenarios and suggests new solid electrolyte and solid-state battery design principles to enhance performance.
Myeloid NCOA4 sequesters KEAP1 to reduce ferroptosis for protection against salmonellosis in mice.
Authors: Xue Xiang , Arcos Mariella , Liu Zhaoli , Villareal Luke , Velez Paloma Kai , Desai Sharina , Noureddine Achraf , Martin David , Brinker C , Zhang Donna
Published: May 2024

Salmonellosis is a severe infection caused by Salmonella enterica serovar Typhimurium, leading to significant global morbidity and mortality. Host nutrition immunity restricts extracellular bacterial replication by reducing iron availability through the induction of the antimicrobial hormone hepcidin. Hepcidin degrades the iron exporter ferroportin, limiting intestinal iron uptake and reducing iron transfer into the blood. Paradoxically, this defense mechanism increases iron storage in macrophages, fostering an environment conducive to intracellular pathogens like Salmonella to proliferate and disseminate. Mice lacking the iron storage protein ferritin heavy chain (FTH1) in myeloid cells exhibit worsened Salmonella infection. Nuclear receptor co-activator 4 (NCOA4) directs FTH1 autophagic degradation to release iron from storage during conditions of low iron. However, the role of myeloid NCOA4 in regulating salmonellosis and gut pathophysiology remains unclear. Here, we reveal that myeloid NCOA4 deficiency augments spleen iron levels and increases cellular iron accumulation, oxidative stress, and ferroptosis in bone marrow-derived macrophages (BMDM) cells. This deficiency also increases susceptibility to Salmonella-induced colitis in mice due to exacerbated oxidative stress and ferroptosis. Mechanistically, NCOA4 suppresses oxidative stress by directly binding to the E3 ubiquitin ligase Kelch-like ECH-associated protein 1 (KEAP1) and stabilizing the antioxidant transcription factor nuclear factor-erythroid 2-related factor 2 (NRF2). Activation of NRF2 protects myeloid NCOA4 knockout mice from Salmonella-induced colitis. Antioxidants Tempol and curcumin offer protection against colitis in myeloid NCOA4-deficient mice. A low iron diet and ferroptosis inhibition also mitigate the heightened colitis in these mice. Overexpression of myeloid cell-specific NCOA4 confers protection against Salmonella-induced colitis via upregulating NRF2 signaling. Together, this study not only advances our understanding of myeloid iron metabolism but also paves the way for novel myeloid cell-targeted therapies to combat salmonellosis.
Designing Molecular RNA Switches with Restricted Boltzmann Machines
Authors: Cocco Simona , Díaz Jorge Fernández de Cossío , Hardouin Pierre , du Moutier Francois-Xavier Lyonnet , Gioacchino Andrea Di , Marchand Bertrand , Ponty Yann , Sargueil Bruno , Monasson Rémi
Published: May 2024

Riboswitches are structured allosteric RNA molecules that change conformation in response to a metabolite binding event, eventually triggering a regulatory response. Computational modelling of the structure of these molecules is complicated by a complex network of tertiary contacts, stabilized by the presence of their cognate metabolite. In this work, we focus on the aptamer domain of SAM-I riboswitches and show that Restricted Boltzmann machines (RBM), an unsupervised ma- chine learning architecture, can capture intricate sequence dependencies induced by secondary and tertiary structure, as well as a switching mechanism between open and closed conformations. The RBM model is then used for the design of artificial allosteric SAM-I aptamers. To experimentally validate the functionality of the designed sequences, we resort to chemical probing (SHAPE-MaP), and develop a tailored analysis pipeline adequate for high-throughput tests of diverse homologous sequences. We probed a total of 476 RBM designed sequences in two experiments, showing between 20% and 40% divergence from any natural sequence, obtaining ≈ 30% success rate of correctly structured aptamers that undergo a structural switch in response to SAM.
Speech Therapy for Poststroke Aphasia: A Systematic Review and Network Meta-Analysis of Randomized Controlled Trials
Authors: Yang Fu-An , Huang Chao-Chun , Lu Chao-Hsien , Wu Pei-Jyuan , Escorpizo Reuben , Chen Hung-Chou
Published: May 2024

Various speech therapies are available for treating poststroke aphasia; however, the effects of these strategies on poststroke aphasia have yet to be compared. We conducted a systematic review and network meta-analysis to investigate the effects of different speech therapies for patients with poststroke aphasia. We searched the PubMed, EMBASE, and Cochrane Library electronic databases from their inception to September 20, 2023. We included trials that (1) involved participants with poststroke aphasia; (2) adopted speech therapy as the intervention; (3) applied either no intervention or another speech therapy as the control treatment; (4) reported speech performance as outcomes. The network meta-analysis was performed using the online tool ShinyNMA (version 1.01). We examined 16 articles involving 775 patients. Our analyses revealed that constraint-induced aphasia therapy (CIAT) prompted significant improvements in speech and motor aphasia performance, whereas computerized speech and language therapy (CSLT) yielded significant improvements in motor aphasia performance. All significant results were also clinically meaningful. No significant inconsistencies were observed between the results of direct and indirect comparisons. Our results suggest CIAT should be the preferred protocol for improving speech performance in patients with poststroke aphasia, with CSLT being a favorable alternative in patients with motor aphasia.
Analysis of the Therapeutic Effectiveness of Segmental Lung Resection Versus Lobectomy in Patients with Isolated Lung Metastases from Colorectal Cancer
Authors: Que Chang-Hao , Jin Dacheng , Wang Qi , Ye ZhiBO , Wang YaPing , Li Chengfang , Lu Peiyuan , Gou yunjiu
Published: May 2024

In patients with solitary pulmonary metastasis from colorectal cancer, surgical resection is considered a standard treatment protocol and routinely performed in thoracic surgery. However, there is a paucity of studies that delve into the detailed discussion of the efficacy and safety of lobectomy and segmentectomy in the treatment of pulmonary metastatic cancer. Our study retrospectively analyzed the surgical outcomes of 62 patients from a single center and reported the findings. In comparison to the group undergoing lung segmental resection, the cohort receiving lobectomy exhibited significantly larger tumor diameters (P < 0.001), prolonged operative durations (P < 0.001), increased intraoperative bleeding (P = 0.002), augmented drainage volume on the first postoperative day (P < 0.001), greater total postoperative drainage (P < 0.001), and elevated operative costs (P < 0.001). Pulmonary segmentectomy offers superior advantages in terms of operative time, intraoperative blood loss, drainage volume on the first postoperative day, total postoperative drainage volume, and surgical costs.
Explainable Gradient Boosting for Corporate Crisis Forecasting in Italian Businesses
Authors: Riccio Donato , Maturo Fabrizio , Mazzitelli Andrea , Bifulco Giuseppe , Paolone Francesco
Published: May 2024

Scholars have taken a keen interest in predicting corporate crises in the past decades. However, most studies focused on classical parametric models that, by their nature, can consider few predictors and interactions and must respect numerous assumptions. Over the past few years, the economy has faced a severe structural crisis that has resulted in significantly lower income, cash, and capital levels than in the past. This crisis has led to insolvency and bankruptcy in many cases. Hence, there is a renewed interest in research for new models for forecasting business crises using novel advanced machine learning techniques. This study aims to develop a model that achieves state-of-the-art accuracy while being fully interpretable, overcoming the limitations of previous research. The model demonstrates excellent predictive performance on par with black-box approaches while maintaining complete transparency by leveraging Explainable Boosting Machines, an intrinsically interpretable tree-based ensemble method, and hyperparameter optimization. The approach automatically considers all possible interactions and uncovers relevant aspects not considered in past studies. This line of research provides compelling results that can bring new insights to the literature on corporate crisis prediction. The interpretable nature of the model is a key advancement, enabling practical application and a deeper understanding of the factors driving corporate financial distress.
Effect of provenance on leaf morphological traits and secondary metabolite levels in leaf extracts of Myrtle (Myrtus communis L.) in Morocco
Authors: SALIM Nora , WAHID Nadya , AABDOUSSE Jamal , OUSSIF Ilias , HAMAMOUCH Noureddine
Published: May 2024

Myrtus communis L. is widely used as an aromatic and medicinal plant. In this work, we investigate the influence of provenance on leaf morphological traits and secondary metabolite levels in leaf extracts of Myrtle. Samples of myrtle from different geographically distinct areas were measured and analysed for polyphenols, flavonoids, condensed tannins, and antioxidant activity using the DPPH test. The analysis of result reveals the significant variance among populations in terms of morphological traits and levels of secondary compounds, particularly in terms of polyphenols, flavonoids, condensed tannins, and reducing power. Correlations between certain studied traits and environmental conditions were recorded. Leaf size and methanolic leaf extract yields from Moroccan myrtle showed as good criteria for natural population selection. Precipitation, temperature, and altitude were determinants of variation in leaf morphological traits, extract yield, and their polyphenolic, tannin, and flavonoid compounds. Based on the studied traits, three major groups were identified with few clear geographical affiliations. The IZA population from the Western Rif and GHA from the Pre-Rif formed a separate group from the other populations, characterized by the highest extract yields. The BRA population from the central plateau formed a distinct isolated group from the others. This population, collected from a location with low annual rainfall values was the richest in tannins with relatively high levels of polyphenols and flavonoids compared to other populations. This means that drought affects the amount of polyphenols and flavonoids. The geographical structure of the third group is mixed, including the IKA and AGH (Pre-Rif) populations, BS and RAB from the Central Plateau, and BT from the Western Rif.
Homeopathic preparations to increase resistance and development of yield in bean (Phaseolus vulgaris) crops
Authors: Correoso Claudio Cordoba , Boff Mari Inês Carissimi , Boff Pedro
Published: May 2024

The common bean (Phaseolus vulgaris) is an essential part people’s staple diet in Brazil as well as in some Latin American countries. The excessive use of agrochemical for pest and disease control negatively impacts human health, contaminates soil and water, harms biodiversity, and contributes to pest resistance. It is referred to a specific homeopathic preparation. In the context of homeopathy, the term "preparations" refers to homeopathic remedies that are created through a specific process of dilution and agitation. The use of highly diluted homeopathic preparations, which enhance the plants ability to resist diseases, represents a more sustainable and environmentally friendly alternative. In homeopathy, "Silicea" is used as a homeopathic remedy derived from silica which is not a silica in its natural form. The objective of this study was to evaluate the effect of Silicea terra and Phosphorus application in high dynamized dilutions, on morphometric and productive variables of common bean plants. Two experiments were carried out in a greenhouse and one experiment in the field, in a randomized block design for both situations. In greenhouse, the preparations were used in dynamizations 7, 12, 24, 36, 48 and 60CH (CH= Hahnemannian centesimal dilution order) and distilled water was used as control. In the field, the treatments were Phosphorus 48 and 60CH, Silicea terra 36 and 60CH, and distilled water as a control. In greenhouse, application of Silicea terra 36CH increased (p< 0.05) shoot dry biomass weight (9.78 g) and leaf dry biomass weight (5.36 g), compared to control. In the field, Silicea terra 36CH and Phosphorus 60CH increased bean productivity in relation to the control. The results indicate that homeopathic preparations had a high potential for improving development and consequently increasing yield when applied to common bean plants.
DESARROLLO DE ESTRATEGIAS EMPRESARIALES SOSTENIBLES CON EL USO DE TECNOLOGÍAS EMERGENTES
Authors: Vera Calderón Tatiana Aracely , Parrales Sánchez Emily Kharimy , Piguave Vargas Mayerli Tatiana , Zambrano Luzardo Jostin Steven
Published: May 2024

Este estudio analiza el desarrollo de estrategias empresariales sostenibles mediante el uso de tecnologías emergentes. Para ello se empleó la revisión de literatura, análisis de datos, revisión de casos de estudio, análisis de tendencias y síntesis de resultados. Entre sus resultados se identificó un creciente reconocimiento de las tecnologías emergentes como motores de sostenibilidad empresarial, con ejemplos destacados como Tesla y Google. Según una encuesta de TechInsights, el 54% de las empresas encuestadas creen que las tecnologías emergentes pueden desempeñar un papel vital en el avance de su progreso hacia la sostenibilidad, mientras que un 41% adicional considera que estas tecnologías tienen un potencial positivo. Por esta razón la adopción de estas tecnologías se presenta como una estrategia clave para mejorar la eficiencia operativa, diferenciarse en el mercado y cumplir con regulaciones ambientales. De este modo, se concluye el potencial de las tecnologías para impulsar la sostenibilidad empresarial y sugiere que su adopción efectiva puede conducir a beneficios económicos, sociales y ambientales significativos.
AUDITORÍA DE OBRAS PÚBLICAS EN EL ECUADOR
Authors: Calle García Aldrin Jefferson , Ángel Soriano Erick Orlando , Sancan Baque Glenda Haylis , Bravo Alcivar María Mailin
Published: May 2024

Este estudio se centra en la auditoría de obras públicas en Ecuador, una temática importante para garantizar la transparencia y eficiencia en la ejecución de proyectos de infraestructura. El objetivo principal es evaluar el proceso de contratación, control del gasto público, calidad y seguridad de las obras. Para ello, se empleó una metodología que incluyó revisión bibliográfica, análisis de datos y estudios de casos. Los resultados indica que el 65% de los contratos de obras públicas en Ecuador presentaron irregularidades en el proceso de contratación, como falta de documentación adecuada, violaciones a los procedimientos de licitación y falta de competitividad en la selección de contratistas. Por otra parte, se encontró que el 45% de los proyectos de obras públicas en el país experimentaron desviaciones significativas en los presupuestos asignados. Además, el 40% de las obras públicas evaluadas presentaron deficiencias en el cumplimiento de normativas y estándares técnicos. En conclusión, se destaca la necesidad de fortalecer los controles y supervisión en la ejecución de proyectos de infraestructura para asegurar el uso eficiente de los recursos públicos y la protección del bienestar de los ciudadanos.
Effects of different flocculants and environment on the flocculation effect of potato starch-processing wastewater
Authors: Suo Na , Li Xiaoqiang , Wu Jian
Published: May 2024

Potato starch-processing wastewater belongs to high-concentration organic wastewater, as direct discharge is more polluting to the environment. Flocculation treatment, as the initial process of wastewater purification, can remove large debris in wastewater, reduce energy consumption for subsequent treatment and reduce production costs. In this study, the effects of traditional flocculants and biological flocculants on the treatment of potato starch-processing wastewater under different pH, dosage, stirring rate and settling time were studied. It was found that traditional flocculants and biological flocculants have their own advantages in the purification ability of organic matter, and the removal rates of suspended solids (SS) and total phosphorus (TP) of traditional flocculants are better than biological flocculants for sweet potato starch-processing wastewater, but the flocculation time and settling time are long. Biological flocculants are environmentally friendly, safe and non-polluting, and do not produce secondary pollution when the flocculation treatment of wastewater is conducive to the secondary reuse of wastewater and flocculation sediment resource treatment. According to the flocculation effect and cost, chitosan is the best flocculant for treating sweet potato starch-processing wastewater.
Human Umbilical Cord Mesenchymal Stem Cell-derived Exosomes Induce
Macrophage M2 Polarization by Antagonizing LPS-mediated Stimulation
of the NF-κB and STAT3 Pathways
Authors: Tian HengJin , Chen AMin , Gao PeiYao , Wang FeiFan , Zhao YanMing , Wang FengChao , Lian Chaoqun , Zhang Qiang
Published: May 2024

Background::

Many studies have documented the protective effects of regulating
macrophage M1/M2 polarization in inflammatory diseases characterized by their imbalance
state. In pathological diseases associated with inflammation, mesenchymal stem cells (MSCs)
regulate macrophages, thereby having anti-inflammatory and tissue regenerative effects. Exosomes
have been suggested as an alternative mechanism that underlies the paracrine function of
MSCs. Thus, this study explored the anti-inflammatory impact of human umbilical cord MSCssecreted
exosomes (hucMSCs-EX) by influencing macrophage polarization in normal and inflammatory
environments in vitro.

Methods::

In this study, hucMSCs-conditioned medium (hucMSCs-CM) and hucMSCs-
EX were used to treat RAW264.7 macrophages with or without LPS. The expressions of TNF-
α, IL-10, IL-6, IL-1β, and Arg-1 were quantified by qPCR. The expressions of IL-6 and IL-10
were evaluated by ELISAs. Western blots (WB) were performed to observe the expressions of
CD206, NF-κB P65, NF-κB p-p65, p-STAT3, STAT3, and NF-κB phosphorylation. The number
of cells expressing CD206 and the fluorescence intensity were measured via flow cytometry
(FC) and immunofluorescence staining. Cell propagation and migration were examined via
MTT and transwell assays, respectively.

Results::

The inhibition of LPS-induced inflammatory polarization by hucMSCs-EX or hucMSCs-
CM led to increases in IL-10 and arginase (Arg) levels and decreases in those of IL-6 and
TNF-α. Moreover, hucMSCs-EX enhanced the CD206 expression in RAW264.7 cells and accelerated
the propagation and migration of LPS-induced cells. The suppressive impact of
hucMSCs-EX on the LPS-induced phenotypic polarization of M1 macrophages was linked
with the reduction of NF-κB signaling. They stimulated the transition of M2 macrophages by
enhancing the activity of STAT3 in RAW264.7 cells.

Conclusion::

This study indicated that hucMSCs-EX enhances the macrophage transition into
the M2 phenotype by inhibiting the NF-κB p65 axis and stimulating that of STAT3.
GPR56, an Adhesion GPCR with Multiple Roles in Human Diseases,
Current Status and Future Perspective
Authors: Fan Yan , Yan Xiao-Yan , Guan Wei
Published: May 2024

:

Human G protein-coupled receptor 56 (GPR56) belongs to a member of the adhesion
G-protein coupled receptor (aGPCR) family and widely exists in the central nervous system and
various types of tumor tissues. Recent studies have shown that abnormal expression or dysfunction
of GPR56 is closely associated with many physiological and pathological processes, including
brain development, neuropsychiatric disorders, cardiovascular diseases and cancer progression.
In addition, GPR56 has been proven to enhance the susceptibility of some antipsychotics and
anticarcinogens in response to the treatment of neuropsychological diseases and cancer. Although
there have been some reports about the functions of GPR56, the underlying mechanisms implicated
in these diseases have not been clarified thoroughly, especially in depression and epilepsy.
Therefore, in this review, we described the molecular structure and signal transduction pathway of
GPR56 and carried out a comprehensive summary of GPR56's function in the development of
psychiatric disorders and cancer. Our review showed that GPR56 deficiency led to depressive-like
behaviors and an increase in resistance to antipsychotic treatment. In contrast, the upregulation of
GPR56 contributed to tumor cell proliferation and metastasis in malignant diseases such as
glioblastoma, colorectal cancer, and ovarian cancer. Moreover, we elucidated specific signaling
pathways downstream of GPR56 related to the pathogenesis of these diseases. In summary, our review
provides compelling arguments for an attractive therapeutic target of GPR56 in improving
the therapeutic efficiency for patients suffering from psychiatric disorders and cancer.
Research Progress of Natural Products with the Activity of Anti-nonalcoholic Steatohepatitis
Authors: Wang Rui , Mao Yuheng , Yu Chunping , Rong Zhenji , Wang Ruyue , Wang Yixin , Lv Linjin , Gao Yang , Wang Zhigang , Zhang Hailong
Published: May 2024

:

Nonalcoholic steatohepatitis (NASH), a multi-target disease, is becoming a global epidemic.
Although several anti-NASH drug candidates are being evaluated in late-stage clinical trials,
none have been approved by the FDA to date. Given the global prevalence of the disease, the lack of
effective drugs, and the very limited therapeutic efficacy of most of the existing synthetic drugs focusing
on a single target, there is an urgent need to continue to develop new therapeutic agents. In
contrast, many natural products, including pure compounds and crude extracts, possess hepatoprotective
activities. Usually, these natural components are characterized by multi-targeting and low
side effects. Therefore, natural products are important resources for the development of new anti-
NASH drugs. In this paper, we focus on reviewing the anti-NASH potential, structure, and some of
the side effects of natural products based on structural classification. We hope this mini-review will
help researchers design and develop new anti-NASH drugs, especially based on the structure of natural
products.
Anticancer Therapy with Proteolysis-targeting Chimeras [PROTACs] Targeting Towards the Tumor-microenvironment: Development, Current
State and Prospects
Authors: Vanangamudi Murugesan , Kaushik Monika , Madeswaraguptha Prathap , Surendran Vijayaraj , Gupta Pawan kumar
Published: May 2024

Targeted protein degradation is a rapidly expanding area that offers hope for novel approaches
to combat drug resistance. The creation of heterobifunctional proteolysis-targeting chimeras
[PROTACs], a new group of pharmaceutical compounds, has made TPD a useful method for completely
getting rid of harmful proteins using regular small-molecule inhibitors. A big plus is that
PROTACs can target multi-domain proteins that cannot be broken down. This is the case, particularly
for proteins lacking a conserved interaction surface for small-molecule ligands [SMIs] and featuring
smooth surfaces. Poor oral bioavailability and pharmacokinetic [PK] and ADMET [absorption, distribution,
metabolism, excretion, and toxicity] characteristics are among the long-term issues with
traditional PROTACs. Their larger size and more complex structure set them apart from other smallmolecule
inhibitors, which is why they are so effective. Clinical studies have been conducted on a
plethora of PROTAC compounds in the past 20 years, all with the goal of inducing the degradation of
targets relevant to cancer. In this article, we closely examine the major developments and recent advancements
in PROTAC technology. We seek to summarize and fully assess PROTAC-based targeted
protein degradation studies on "undruggable" targets. Discussing their molecular structure, action
mechanism, design concepts, development benefits, and obstacles will help to illustrate the significance
of developing highly successful PROTAC-based techniques in treating many illnesses, including
cancer treatment resistance.
Persistent Inflammation, Immunosuppression, and Catabolism Syndrome in Pediatric Populations: A Brief Perspective
Authors: Santarelli Michael D. , Davis Kelly A. , Stark Ryan J.
Published: May 2024

Surviving near-lethal insults, such as sepsis, trauma, and major surgery is more common
due to advances in medical care. The decline in mortality has unmasked a population of
chronic critically ill patients, many with the pathological immunophenotype known as Persistent
inflammation, Immunosuppression, and Catabolism Syndrome (PICS). Though initially described
in adults, many critically ill children exhibit the hallmarks of PICS, including lymphopenia, hyperinflammation,
and evidence of ongoing somatic protein catabolism. These patients are plagued
with recurrent infections and suffer worse outcomes. There remains a need to understand the
pathophysiology underlying this condition to elucidate potential therapies and develop interventions.
This perspective provides the most current update of PICS within the pediatric population.
Virtual Analysis for Spinal Cord Injury Rehabilitation
Authors: Narendra Modigari , Mohanty Pratik , Anbarasi L Jani , Ravi Vinayakumar
Published: May 2024

Background

Spinal cord injuries (SCI) are debilitating conditions affecting individuals worldwide annually, leading to physical, emotional, and cognitive challenges. Effective rehabilitation for SCI patients is crucial for restoring motor function and enhancing their overall quality of life. Advances in technology, including machine learning (ML) and computer vision, offer promising avenues for personalized SCI treatment.

Aims

This paper aimed to propose an automated and cost-effective system for spinal cord injury (SCI) rehabilitation using machine learning techniques, leveraging data from the Toronto Rehab Pose dataset and Mediapipe for real-time tracking.

Objective

The objective is to develop a system that predicts rehabilitation outcomes for upper body movements, highlighting the transformative role of ML in personalized SCI treatment and offering tailored strategies for improved outcomes.

Methods

The proposed system utilized data from the Toronto Rehab Pose dataset and Mediapipe for real-time tracking. Machine learning models, including Support Vector Machines (SVM), Logistic Regression, Naive Bayes, and XGBoost, were employed for outcome prediction. Features such as joint positions, angles, velocities, and accelerations were extracted from movement data to train the models.

Results

Statistical analysis revealed the ability of the system to accurately classify rehabilitation outcomes, with an average accuracy of 98.5%. XGBoost emerged as the top-performing algorithm, demonstrating superior accuracy and precision scores across all exercises.

Conclusion

This paper emphasizes the importance of continuous monitoring and adjustment of rehabilitation plans based on real-time progress data, highlighting the dynamic nature of SCI rehabilitation and the need for adaptive treatment strategies. By predicting rehabilitation outcomes with high accuracy, the system enables clinicians to devise targeted interventions, optimizing the efficacy of the rehabilitation process.
In Silico Prediction of Quercetin Analogs for Targeting Death-Associated Protein Kinase 1 (DAPK1) Against Alzheimer’s Disease
Authors: Sun Yilu , Zhao Jia , Lu Yizhu , Ngo Fung Yin , Shuai Bo , Zhang Zhang-Jin , Feng Yibin , Rong Jianhui
Published: May 2024

:

Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder that greatly affects
the health and life quality of the elderly population. Existing drugs mainly alleviate symptoms but fail
to halt disease progression, underscoring the urgent need for the development of novel drugs. Based
on the neuroprotective effects of flavonoid quercetin in AD, this study was designed to identify potential AD-related targets for quercetin and perform in silico prediction of promising analogs for the
treatment of AD. Database mining suggested death-associated protein kinase 1 (DAPK1) as the most
promising AD-related target for quercetin among seven protein candidates. To achieve better biological effects for the treatment of AD, we devised a series of quercetin analogs as ligands for DAPK1,
and molecular docking analyses, absorption, distribution, metabolism, and excretion (ADME) predictions, as well as molecular dynamics (MD) simulations, were performed. The energy for drug-protein
interaction was predicted and ranked. As a result, quercetin-A1a and quercetin-A1a1 out of 19 quercetin analogs exhibited the lowest interaction energy for binding to DAPK1 than quercetin, and they had
similar dynamics performance with quercetin. In addition, quercetin-A1a and quercetin-A1a1 were
predicted to have better water solubility. Thus, quercetin-A1a and quercetin-A1a1 could be promising
agents for the treatment of AD. Our findings paved the way for further experimental studies and the
development of novel drugs.
Interactive Health Technology Tool for Kidney Living Donor Assessment to Standardize the Informed Consent Process: Usability and Qualitative Content Analysis
Authors: Ortiz Fernanda , Grasberger Juulia , Ekstrand Agneta , Helanterä Ilkka , Giunti Guido
Published: May 2024

Background

Kidney living donation carries risks, yet standardized information provision regarding nephrectomy risks and psychological impacts for candidates remains lacking.

Objective

This study assesses the benefit of interactive health technology in improving the informed consent process for kidney living donation.

Methods

The Kidney Hub institutional open portal offers comprehensive information on kidney disease and donation. Individuals willing to start the kidney living donation process at Helsinki University Hospital (January 2019-January 2022) were invited to use the patient-tailored digital care path (Living Donor Digital Care Path) included in the Kidney Hub. This platform provides detailed donation process information and facilitates communication between health care professionals and patients. eHealth literacy was evaluated via the eHealth Literacy Scale (eHEALS), usability with the System Usability Scale (SUS), and system utility through Likert-scale surveys with scores of 1-5. Qualitative content analysis addressed an open-ended question.

Results

The Kidney Hub portal received over 8000 monthly visits, including to its sections on donation benefits (n=1629 views) and impact on donors’ lives (n=4850 views). Of 127 living kidney donation candidates, 7 did not use Living Donor Digital Care Path. Users’ ages ranged from 20 to 79 years, and they exchanged over 3500 messages. A total of 74 living donor candidates participated in the survey. Female candidates more commonly searched the internet about kidney donation (n=79 female candidates vs n=48 male candidates; P=.04). The mean eHEALS score correlated with internet use for health decisions (r=0.45; P<.001) and its importance (r=0.40; P=.01). Participants found that the Living Donor Digital Care Path was technically satisfactory (mean SUS score 4.4, SD 0.54) and useful but not pivotal in donation decision-making. Concerns focused on postsurgery coping for donors and recipients.

Conclusions

Telemedicine effectively educates living kidney donor candidates on the donation process. The Living Donor Digital Care Path serves as a valuable eHealth tool, aiding clinicians in standardizing steps toward informed consent.

Trial Registration

ClinicalTrials.gov NCT04791670; https://clinicaltrials.gov/study/NCT04791670

International Registered Report Identifier (IRRID)

RR2-10.1136/bmjopen-2021-051166
Participatory Disease Surveillance for the Early Detection of Cholera-Like Diarrheal Disease Outbreaks in Rural Villages in Malawi: Prospective Cohort Study
Authors: Valerio Mariana Gasparoto Pereira , Laher Beverly , Phuka John , Lichand Guilherme , Paolotti Daniela , Leal Neto Onicio
Published: May 2024

Background

Cholera-like diarrheal disease (CLDD) outbreaks are complex and influenced by environmental factors, socioeconomic conditions, and population dynamics, leading to limitations in traditional surveillance methods. In Malawi, cholera is considered an endemic disease. Its epidemiological profile is characterized by seasonal patterns, often coinciding with the rainy season when contamination of water sources is more likely. However, the outbreak that began in March 2022 has extended to the dry season, with deaths reported in all 29 districts. It is considered the worst outbreak in the past 10 years.

Objective

This study aims to evaluate the feasibility and outcomes of participatory surveillance (PS) using interactive voice response (IVR) technology for the early detection of CLDD outbreaks in Malawi.

Methods

This longitudinal cohort study followed 740 households in rural settings in Malawi for 24 weeks. The survey tool was designed to have 10 symptom questions collected every week. The proxies’ rationale was related to exanthematic, ictero-hemorragica for endemic diseases or events, diarrhea and respiratory/targeting acute diseases or events, and diarrhea and respiratory/targeting seasonal diseases or events. This work will focus only on the CLDD as a proxy for gastroenteritis and cholera. In this study, CLDD was defined as cases where reports indicated diarrhea combined with either fever or vomiting/nausea.

Results

During the study period, our data comprised 16,280 observations, with an average weekly participation rate of 35%. Maganga TA had the highest average of completed calls, at 144.83 (SD 10.587), while Ndindi TA had an average of 123.66 (SD 13.176) completed calls. Our findings demonstrate that this method might be effective in identifying CLDD with a notable and consistent signal captured over time (R2=0.681404). Participation rates were slightly higher at the beginning of the study and decreased over time, thanks to the sensitization activities rolled out at the CBCCs level. In terms of the attack rates for CLDD, we observed similar rates between Maganga TA and Ndindi TA, at 16% and 15%, respectively.

Conclusions

PS has proven to be valuable for the early detection of epidemics. IVR technology is a promising approach for disease surveillance in rural villages in Africa, where access to health care and traditional disease surveillance methods may be limited. This study highlights the feasibility and potential of IVR technology for the timely and comprehensive reporting of disease incidence, symptoms, and behaviors in resource-limited settings.
Sample Size Considerations for Fine-Tuning Large Language Models for Named Entity Recognition Tasks: Methodological Study
Authors: Majdik Zoltan P , Graham S Scott , Shiva Edward Jade C , Rodriguez Sabrina N , Karnes Martha S , Jensen Jared T , Barbour Joshua B , Rousseau Justin F
Published: May 2024

Background

Large language models (LLMs) have the potential to support promising new applications in health informatics. However, practical data on sample size considerations for fine-tuning LLMs to perform specific tasks in biomedical and health policy contexts are lacking.

Objective

This study aims to evaluate sample size and sample selection techniques for fine-tuning LLMs to support improved named entity recognition (NER) for a custom data set of conflicts of interest disclosure statements.

Methods

A random sample of 200 disclosure statements was prepared for annotation. All “PERSON” and “ORG” entities were identified by each of the 2 raters, and once appropriate agreement was established, the annotators independently annotated an additional 290 disclosure statements. From the 490 annotated documents, 2500 stratified random samples in different size ranges were drawn. The 2500 training set subsamples were used to fine-tune a selection of language models across 2 model architectures (Bidirectional Encoder Representations from Transformers [BERT] and Generative Pre-trained Transformer [GPT]) for improved NER, and multiple regression was used to assess the relationship between sample size (sentences), entity density (entities per sentence [EPS]), and trained model performance (F1-score). Additionally, single-predictor threshold regression models were used to evaluate the possibility of diminishing marginal returns from increased sample size or entity density.

Results

Fine-tuned models ranged in topline NER performance from F1-score=0.79 to F1-score=0.96 across architectures. Two-predictor multiple linear regression models were statistically significant with multiple R2 ranging from 0.6057 to 0.7896 (all P<.001). EPS and the number of sentences were significant predictors of F1-scores in all cases ( P<.001), except for the GPT-2_large model, where EPS was not a significant predictor (P=.184). Model thresholds indicate points of diminishing marginal return from increased training data set sample size measured by the number of sentences, with point estimates ranging from 439 sentences for RoBERTa_large to 527 sentences for GPT-2_large. Likewise, the threshold regression models indicate a diminishing marginal return for EPS with point estimates between 1.36 and 1.38.

Conclusions

Relatively modest sample sizes can be used to fine-tune LLMs for NER tasks applied to biomedical text, and training data entity density should representatively approximate entity density in production data. Training data quality and a model architecture’s intended use (text generation vs text processing or classification) may be as, or more, important as training data volume and model parameter size.
Distributed Analytics for Research in Hospitals (DARAH): Federated Analysis with Differential Privacy in a Real-World Oncology Study (Preprint)
Authors: Riffel Théo , Créquit Perrine , Baillet Maëlle , Paumier Jason , Marfoq Yasmine , Sy Ronan , Girardot Olivier , Chanet Thierry , Bayssat Louise , Mazières Julien , Vuiblet Vincent , Ancel Julien , Dewolf Maxime , Margraff François , Bachot Camille , Chmiel Jacek
Published: May 2024

BACKGROUND

Federated analytics in healthcare allows researchers to perform statistical queries on remote data sets without access to the raw data. This method arose from the need to perform statistical analysis on larger datasets collected at multiple healthcare centers while avoiding regulatory, governance, and privacy issues that might arise if raw data were collected at a central location outside the healthcare centers. Despite some pioneering work, federated analytics is still not widely used on real-world data, and to our knowledge, no real-world study has yet combined it with other privacy-enhancing techniques such as differential privacy.federated analysis, differential privacy, real-world oncology study, non-small cell lung cancer, COVID-19federated analysis, differential privacy, real-world oncology study, non-small cell lung cancer, COVID-19

OBJECTIVE

The first objective of this study was to deploy a federated architecture in a real-world setting. The oncology study used for this deployment compared the medical healthcare management of patients with metastatic non-small cell lung cancer before and during/after the 1st wave of COVID-19. The second goal was to test differential privacy in this real-world scenario to assess its practicality and utility as a privacy enhancing technology.

METHODS

A federated architecture platform was set up in the Toulouse, Reims and Foch centers. After harmonization of the data in each center, statistical analyses were performed using DataSHIELD, a federated analysis R library and a new open source differential privacy DataSHIELD package was implemented: dsPrivacy.

RESULTS

50 patients were enrolled in the Toulouse and Reims centers and 49 in the Foch center. We have shown that DataSHIELD is a practical tool to efficiently conduct our study across all 3 centers without exposing data on a central node, once sufficient setup has been made to configure a secure network between hospitals. All planned aggregated results were successfully generated. We also observed that differential privacy can be implemented in practice with promising trade-offs between privacy and accuracy, and we built a library that will prove useful for future work.

CONCLUSIONS

The federated architecture platform enabled a multicenter study to be conducted on real-world oncology data with strong privacy guarantees thanks to differential privacy.
Advancing Preeclampsia Prediction: A Tailored Machine Learning Pipeline for Handling Imbalanced Medical Data (Preprint)
Authors: Ma Yinyao , Lv Hanlin , Ma Yanhua , Wang Xiao , Lv Longting , Liang Xuxia , Wang Lei
Published: May 2024

BACKGROUND

Preeclampsia represents a significant challenge in obstetrics. Effective early prediction is crucial for timely intervention, yet the development of predictive models is complicated by the class imbalances inherent in clinical data.

OBJECTIVE

This study aims to develop a robust pipeline that enhances the predictive performance of ensemble machine learning models for the early prediction of preeclampsia in an imbalanced dataset.

METHODS

We evaluated combinations of six ensemble machine learning algorithms and eight resampling techniques across a spectrum of minority-to-majority ratios. Using statistical methods, we systematically identified and optimized these configurations, focusing on key performance metrics such as Geometric Mean.

RESULTS

The strategic optimization of variable selection and settings proved crucial. The configuration using the Inverse Weighted Gaussian Mixture Model for resampling, followed by the Gradient Boosting Decision Trees algorithm, with an optimized minority-to-majority ratio of 0.09, was identified as the most effective, achieving a Geometric Mean of 0.6694. This configuration significantly outperformed the baseline across all evaluated metrics, demonstrating substantial improvements in model performance.

CONCLUSIONS

This study establishes a robust pipeline that significantly enhances the predictive performance of models for preeclampsia within imbalanced datasets. Our findings underscore the importance of a strategic approach to variable optimization in medical diagnostics, offering potential for broad application in various medical contexts where class imbalance is a concern.
CLINICAL PRESENTATION AND MANAGEMENT OF DENGUE IN PEDIATRIC PATIENTS
Authors: HASEEB ABDUL , SHARANABASAPPA  , HAREESH
Published: May 2024

Objective: Dengue fever poses a significant challenge to global health, particularly affecting children in endemic regions. The diverse clinical presentations, ranging from mild to severe forms such as dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS), complicate its diagnosis and management in pediatric populations. Understanding the clinical nuances is crucial, given the substantial global burden of dengue.
Methods: This prospective cross-sectional study conducted at the Department of Pediatrics, Yashoda Super Specialty Hospital, aimed to investigate the clinical, laboratory, and radiological features of dengue fever in pediatric patients aged 6 mo to 16 y. Data collection involved demographic details, clinical presentations, laboratory findings, and treatment administered. Statistical analysis was performed using SPSS version 19.0.
Results: Among the 100 enrolled pediatric patients, high fever (100%), headache (75%), myalgia (70%), rash (65%), and hemorrhagic manifestations (40%) were prevalent clinical features. Laboratory findings revealed thrombocytopenia in 60% of cases and elevated liver enzymes in 30%. Correlation analyses identified associations between specific symptoms and diagnostic findings, aiding in the recognition of severe cases such as DSS.
Conclusion: The study highlights the diverse clinical spectrum of pediatric dengue, emphasizing the importance of vigilant clinical assessment and laboratory testing for timely diagnosis and management. These insights are essential for optimizing patient care and outcomes, particularly in endemic regions.