bluuebunny/crossref_metadata_2025 huggingface dataset:
Case report: Brain infarction following percutaneous drainage of a liver abscess post-chemotherapy for pancreatic head cancer
Authors: Deng Wan-qiu , Wei Bo , Li Zheng-yan , Liu Kai
Published: December 2024

Bacterial liver abscesses commonly occur in patients with immune deficiencies such as diabetes, post-chemotherapy, or post-immunosuppressive therapy. The recommended treatment for liver abscesses exceeding 5 cm in a diameter is anti-infection therapy combined with percutaneous catheter drainage. Complications may include local spread to adjacent tissues or organs and thrombosis of the liver and portal veins. Rare hematogenous spread to distant sites, such as endophthalmitis and central nervous system embolism, have been reported, though such complications are uncommon post-drainage. This case report details a patient who suffered a brain infarction shortly after percutaneous drainage of a large liver abscess.
Development and validation of clinical criteria for critical illness-associated immune dysfunction: based on the MIMIC-IV database
Authors: Zhou Yanyou , Tao Linfeng , Yang Shengsheng , Li Juntu , Liu Jun
Published: December 2024

Background

Critical illness-associated immune dysfunction (CIID) is prevalent in the ICU and frequently resulted in uncontrollably immune responses. Critical immunological dysfunction is understood to be important, although there are currently no clinically accepted diagnostic criteria for it. Given this, we examined the literature and developed an initial diagnostic criterion that we validated using the MIMIC-IV database.

Methods

We searched the related literature in the last 32 years. Patients admitted to the ICU for the first time were selected by screening the MIMIC-IV database. Different criteria were used to categorize patients into groups related to immune dysfunction (ID) and non-immune dysfunction (NID). Within the ID group, patients were subdivided into three subgroups: hyperinflammatory (HI), immunosuppression (IS), and a subgroup combining immunosuppression and hyperinflammation (HI+IS). The APACHE II was used to measure the patients’ severity. The association between immune dysfunction and mortality after 30 or 180 days was evaluated through the KM curves and COX regression analysis.

Results

By summarizing relevant literature, we proposed the initial diagnostic criteria. The analysis included 43,965 patients, with approximately 77% meeting the diagnostic criteria for CIID. We observed that patients with immune dysfunction possessed higher APACHE II scores and there were differences in peak APACHE II among the three subgroups. When comparing patients’ 30-day mortality in the COX model, it is evident that patients in the IS subgroup had the lowest risk and patients in the HI subgroup the greatest risk after accounting for all covariates. In contrast, patients in the IS subgroup had the highest risk of death, those in the HI subgroup had the lowest risk when comparing long-term mortality. In summary, we propose and validate diagnostic criteria related to CIID. Subgroup analyses were carried out, which also revealed variations between the three groups.

Conclusion

The diagnostic criteria were confirmed by the MIMIC-IV database, demonstrating the diagnostic criteria were scientifically valid and reliable.
Red cell distribution width to albumin ratio is associated with asthma risk: a population-based study
Authors: Ding Jinzhen , Zhang Yixiang , Chen Xiaoyang
Published: December 2024

Background

The red cell distribution width to albumin ratio (RAR), a newly identified biomarker of inflammation, has been linked to a variety of inflammatory diseases. Asthma, a major burden on global health, is an inflammatory airway disease that is profoundly affected by inflammation. This study primarily sought to examine the influence of RAR on the risk of developing asthma.

Methods

Data from 1999 to 2020 was gathered from the NHANES database. The impact of RAR on asthma risk and their non-linear relationship were clarified by multivariate logit and restricted cubic spline (RCS) analyses. Subgroup and interaction analyses collectively formed the sensitivity analysis for this study.

Results

This study was based on an analysis of 54,161 individuals. RAR has been identified as an independent risk factor for asthma, according to logit analysis. The moderate and high RAR groups had a 16% [95% confidence interval (CI): 1.06–1.27] and 43% (95% CI: 1.30–1.58) higher risk, respectively, compared to the lowest group. Every 0.5 unit increase in RAR almost doubled the risk of asthma [odds ratio (OR): 1.82, 95% CI: 1.55–2.12]. There was no non-linear relationship between RAR and asthma risk, based on RCS analysis. Combining subgroup and interaction analyses results, all subgroups in this study showed consistent trends with the overall population.

Conclusion

Notably, this article, the first to examine the relationship between RAR and asthma risk, unveiled a positive linear correlation between them. With an increase in RAR, whether analyzed as a categorical or continuous variable, asthma risk significantly increases. This finding was beneficial for clinicians to anticipate and assess the onset of asthma through stratified or dynamic management. Given RAR’s numerous advantages, its application in clinical settings held considerable promise.
Weakly supervised learning in thymoma histopathology classification: an interpretable approach
Authors: Wang Chunbao , Du Xianglong , Yan Xiaoyu , Teng Xiali , Wang Xiaolin , Yang Zhe , Chang Hongyun , Fan Yangyang , Ran Caihong , Lian Jie , Li Chen , Li Hansheng , Cui Lei , Jiang Yina
Published: December 2024

Introduction

Thymoma classification is challenging due to its diverse morphology. Accurate classification is crucial for diagnosis, but current methods often struggle with complex tumor subtypes. This study presents an AI-assisted diagnostic model that combines weakly supervised learning with a divide-and-conquer multi-instance learning (MIL) approach to improve classification accuracy and interpretability.

Methods

We applied the model to 222 thymoma slides, simplifying the five-class classification into binary and ternary steps. The model features an attention-based mechanism that generates heatmaps, enabling visual interpretation of decisions. These heatmaps align with clinically validated morphological differences between thymoma subtypes. Additionally, we embedded domain-specific pathological knowledge into the interpretability framework.

Results

The model achieved a classification AUC of 0.9172. The generated heatmaps accurately reflected the morphological distinctions among thymoma subtypes, as confirmed by pathologists. The model's transparency allows pathologists to visually verify AI decisions, enhancing diagnostic reliability.

Discussion

This model offers a significant advancement in thymoma classification, combining high accuracy with interpretability. By integrating weakly supervised learning, MIL, and attention mechanisms, it provides an interpretable AI framework that is applicable in clinical settings. The model reduces the diagnostic burden on pathologists and has the potential to improve patient outcomes by making AI tools more transparent and clinically relevant.
Synergy and competition during the anaerobic degradation of N-acetylglucosamine in a methane-emitting, subarctic, pH-neutral fen
Authors: Kujala Katharina , Schmidt Oliver , Horn Marcus A.
Published: December 2024

Peatlands are invaluable but threatened ecosystems that store huge amounts of organic carbon globally and emit the greenhouse gasses carbon dioxide (CO2) and methane (CH4). Trophic interactions of microbial groups essential for methanogenesis are poorly understood in such systems, despite their importance. Thus, the present study aimed at unraveling trophic interactions between fermenters and methanogens in a nitrogen-limited, subarctic, pH-neutral fen. In situ CH4 emission measurements indicated that the fen is a source of CH4, and that CH4 emissions were higher in plots supplemented with ammonium compared to unsupplemented plots. The amino sugar N-acetylglucosamine was chosen as model substrate for peat fermenters since it can serve as organic carbon and nitrogen source and is a monomer of chitin and peptidoglycan, two abundant biopolymers in the fen. Supplemental N-acetylglucosamine was fermented to acetate, ethanol, formate, and CO2 during the initial incubation of anoxic peat soil microcosms without preincubation. Subsequently, ethanol and formate were converted to acetate and CH4. When methanogenesis was inhibited by bromoethanesulfonate, acetate and propionate accumulated. Long-term preincubation considerably increased CH4 production in unsupplemented microcosms and microcosms supplemented with methanogenic substrates. Supplemental H2-CO2 and formate stimulated methanogenesis the most, whereas acetate had an intermediary and methanol a minor stimulatory effect on methane production in preincubated microcosms. Activity of acetogens was suggested by net acetate production in microcosms supplemented with H2-CO2, formate, and methanol. Microbial community analysis of field fresh soil indicated the presence of many physiologically unresolved bacterial taxa, but also known primary and secondary fermenters, acetogens, iron reducers, sulfate reducers, and hydrogenotrophic methanogens (predominately Methanocellaceae and Methanoregulaceae). Aceticlastic methanogens were either not abundant (Methanosarcinaceae) or could not be detected due to limited coverage of the used primers (Methanotrichaceae). The collective results indicate a complex interplay of synergy and competition between fermenters, methanogens, acetogens, and potentially iron as well as sulfate reducers. While acetate derived from fermentation or acetogenesis in this pH-neutral fen likely plays a crucial role as carbon source for the predominant hydrogenotrophic methanogens, it remains to be resolved whether acetate is also converted to CH4 via aceticlastic methanogenesis and/or syntrophic acetate oxidation coupled to hydrogenotrophic methanogenesis.
Spatiotemporal distributions, co-occurrence networks, and assembly mechanisms of the bacterial community in sediments of the Yangtze River: comprehensive insights into abundant and rare taxa
Authors: Zhang Guohua , Liu Shufeng , Du Wenran , Li Yinghao , Wu Zongzhi , Liu Tang , Wang Yichu
Published: December 2024

Sediments are key reservoirs for rare bacterial biospheres that provide broad ecological services and resilience in riverine ecosystems. Compared with planktons, there is a lack of knowledge regarding the ecological differences between abundant and rare taxa in benthic bacteria along a large river. Here, we offer comprehensive insights into the spatiotemporal distributions, co-occurrence networks, and assembly processes of three divided categories namely always rare taxa (ART), conditionally rare taxa (CRT), and conditionally rare and abundant taxa (CRAT) in sediments covering a distance of 4,300 km in the Yangtze River. Our study demonstrated that ART/CRT contributed greatly to the higher Chao-1 index, Shannon-Wiener index, and phylogenetic alpha diversity of benthic bacteria in autumn than in spring. ART showed high overall beta diversity, and CRT/CRAT exhibited more significant distance-decay patterns than ART in both seasons, mainly corresponding to macroscopic landform types. CRT predominated the nonrandom co-occurrence network, with 97% of the keystone species mostly affiliated with Acidobacteriota flourishing in the lower-reach plain. Two selection processes had the greatest influences on the assembly of CRT (74.7–77.6%), whereas CRAT were driven primarily by dispersal limitation (74.9–86.8%) and ART were driven by heterogeneous selection (33.9–48.5%) and undominated stochasticity (32.7–36.5%). Natural factors such as river flow and channel slope exhibited more significant correlations with community variation than nutrients in all three groups, and total organic carbon mediated the balance among the distinct assembly processes of the ART and CRT in both seasons. Taken together, these results provide an improved ecological understanding of the discrepancy in biogeographic patterns between abundant and rare bacterial taxa in the sediments of Asia’s largest river.
Improvement of silage characteristics of Lactobacillus salivarius HMC4 and improvement of silage quality of king grass
Authors: Yang Jinsong , Zhao Songsong , Zhi Wenbo , Lu Tianyu , Qiao Huahua , Liu Wei , Dou Ying , Tan Haisheng , Zhou Hanlin
Published: December 2024

The effect of HMC4 produced by protoplast fusion on silage was studied. The silage formula was composed of heterozygote HMC4 (Group C), parent Lactobacillus (Group A) and a combination of two parents (Group B). The fermentation quality and microbial composition of each batch of silage were evaluated. The results showed that the propionic acid concentration in group C was the lowest, but the organic acid content in feed was significantly increased. Groups B and C had slightly lower crude fiber levels than group A, while groups A and C had higher levels of soluble sugars. The dynamic observation of C group showed that the nutrient composition of feed changed gradually with the extension of silage period. High-throughput sequencing revealed fluctuations in microbial composition before and after silage. Over time, Lactobacillus became the dominant strain and its numbers steadily increased.
Managing tomato bacterial wilt through pathogen suppression and host resistance augmentation using microbial peptide
Authors: Tiwari Ishan , Bhojiya Ali Asger , Jain Devendra , Kothari S. L. , El-Sheikh Mohamed A. , Porwal Shalini
Published: December 2024

The increasing health and environmental risks associated with synthetic chemical pesticides necessitate the exploration of safer, sustainable alternatives for plant protection. This study investigates a novel biosynthesized antimicrobial peptide (AMP) from Lactiplantibacillus argentoratensis strain IT, identified as the amino acid chain PRKGSVAKDVLPDPVYNSKLVTRLINHLMIDGKRG, for its efficacy in controlling bacterial wilt (BW) disease in tomato (Solanum lycopersicum) caused by Ralstonia solanacearum. Our research demonstrates that foliar application of this AMP at a concentration of 200 ppm significantly reduces disease incidence by 49.3% and disease severity by 45.8%. Scanning electron microscopy revealed severe morphological disruptions in the bacterial cells upon exposure to the AMP. Additionally, the AMP enhanced host resistance by elevating defense enzyme activities, leading to notable improvements in plant morphology, including a 95.5% increase in plant length, a 20.1% increase in biomass, and a 96.69% increase in root length. This bifunctional AMP provides dual protection by exerting direct antimicrobial activity against the pathogen and eliciting plant defense mechanisms. These findings underscore the potential of this biologically sourced AMP as a natural agent for combating plant diseases and promoting growth in tomato crops. To the best of our knowledge, this is the first study to demonstrate the use of a foliar spray application of a biosynthesized microbial peptide as biocontrol agent against R. solanacearum. This interaction not only highlights its biocontrol efficacy but also its role in promoting the growth of Solanum lycopersicum thereby increasing overall agricultural yield.
Weizmannia coagulans BC99 alleviates hyperuricemia and oxidative stress via DAF-16/SKN-1 activation in Caenorhabditis elegan
Authors: Gao Yinyin , Li Cheng , Li Junfei , Duan Mengyao , Li Xuan , Zhao Lina , Wu Ying , Gu Shaobin
Published: December 2024

Introduction

Hyperuricemia (HUA) refers to the presence of excess uric acid (UA) in the blood, which increases the risk of chronic kidney disease and gout. Probiotics have the potential to alleviate HUA.

Methods

This study established a hyperuricemia model using Caenorhabditis elegans (C. elegans), and studied the anti-hyperuricemia activity and potential mechanisms of Weizmannella coagulans BC99 (W. coagulans) at different concentrations (107 CFU/mL BC99, 108 CFU/mL BC99). Subsequently, we utilized UPLC-Q-TOF/MS to investigate the impact of BC99 on endogenous metabolites in C. elegans and identified pathways and biomarkers through differential metabolomics analysis.

Results

The results of this study showed that BC99 treatment significantly reduced the expression of P151.2 and T22F3.3 (p < 0.05), reduced the levels of UA and xanthine oxidase (XOD) in nematodes (p < 0.05), while extending their lifespan and movement ability (p < 0.05). Mechanistically, BC99 activates the transcription factors DAF-16 and SKN-1, thereby inducing the expression of stress response genes, enhancing the activity of antioxidant enzymes and tolerance to heat stress in the body, and reducing the production of ROS (p < 0.001). This effect was most significant in the H-BC99 group. Furthermore, non-targeted metabolomics indicated that BC99 predominantly regulated pathways associated with amino acid metabolism (Carnosine), glycerophospholipid metabolism, and purine metabolism.

Discussion

These results underscore BC99 as an effective and economical adjunct therapeutic agent for hyperuricemia, providing a scientific basis for further development and application.
Porcine peritoneal macrophages are susceptible to porcine reproductive and respiratory syndrome virus infection
Authors: Durazo-Martinez Kassandra , Chaudhari Jayeshbhai , Kumari Sushmita , Vu Hiep L. X.
Published: December 2024

Previous studies have suggested that porcine peritoneal macrophages (PPMs) are resistant to PRRSV infection, whereas porcine alveolar macrophages (PAMs) are highly susceptible. This contrast is intriguing, as both cell types belong to the same monocyte/macrophage family. The current study aimed to investigate the host factors contributing to the differing susceptibility of PPMs and PAMs to PRRSV infection. We found that PPMs exhibit a higher frequency of CD14+ cells compared to PAMs, suggesting a more immature macrophage phenotype in PPMs. Importantly, PPMs expressed both CD163 and CD169, the key receptors for PRRSV entry, although the frequency and intensity of CD163 and CD169 expression were lower in PPMs than in PAMs. Despite these differences, PPMs were susceptible to both PRRSV-1 and PRRSV-2 isolates. Notably, PPMs susceptibility increased 10-fold when the cells were cultured for 1 day before infection. PRRSV infection in PPMs was dependent on CD163, as pretreatment with an anti-CD163 antibody significantly reduced infection. Overall, our results demonstrate that PPMs are susceptible to PRRSV infection, thereby expanding the understanding of PRRSV tropism.
Sociodemographic factors and comorbidities are associated with an elevated risk of herpes simplex keratitis: a population-based study in Taiwan
Authors: Jan Ren-Long , Ho Chung-Han , Wang Jhi-Joung , Jan Han-Yi , Chen Jiun-Yi , Chang Yuh-Shin
Published: December 2024

To investigate the association among comorbidities, sociodemographic factors, and herpes simplex keratitis (HSK). This nationwide, population-based, retrospective, matched case-control study included 27,651 patients with HSK identified from the Taiwan National Health Insurance Research Database based on the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code 054.42 for dendritic keratitis and 054.43 for herpes simplex disciform keratitis. The age-, sex-, and index date-matched control group included 27,651 non-HSK individuals selected from the Taiwan Longitudinal Health Insurance Database 2000. Associations between HSK, sociodemographic conditions, and comorbidities were examined using univariate logistic regression analyses, and paired t-tests were used for continuous variables. Adjusted logistic regression was used to compare odds ratios (OR) for HSK development. Patients with corneal abrasion were more likely to develop HSK than controls [OR, 402.80; 95% confidence interval (CI), 167.47–968.79; P < 0.0001] even after conditional logistic regression (adjusted OR, 407.36; 95% CI, 169.35–979.89; P < 0.0001). Other conditions that increase the odds of HSK development include systemic diseases such as hyperlipidemia, diabetes mellitus, coronary artery disease, chronic renal disease, and human immunodeficiency virus infection. Regarding sociodemographic factors, >50% of patients with HSK were aged ≥55 years. Moreover, patients living in Northern Taiwan and metropolitan cities had higher odds of developing HSK. HSK is significantly associated with corneal abrasion, hyperlipidemia, diabetes mellitus, coronary artery disease, chronic renal disease, and human immunodeficiency virus infection.
Pathological mechanisms of glial cell activation and neurodegenerative and neuropsychiatric disorders caused by Toxoplasma gondii infection
Authors: Yang Zihan , Chen Jiating , Zhang Chi , Peng Hongjuan
Published: December 2024

Toxoplasma gondii is an intracellular opportunistic parasite that exists in a latent form within the human central nervous system (CNS), even in immune-competent hosts. During acute infection, T. gondii traverses the blood–brain barrier (BBB). In the subsequent chronic infection phase, the infiltration of immune cells into the brain, driven by T. gondii infection and the formation of parasitic cysts, leads to persistent activation and proliferation of astrocytes and microglia. This process results in neuronal damages that are fatal in some cases. Through inducing systemic immune responses, T. gondii infection can dramatically alter the behavior of rodents and increase the risk of various neuropsychiatric disorders in humans. In this review, we explore some recent research progress on the major events involved in BBB disruption, glial cell activation and neuronal damage following T. gondii infection in hosts. It further discusses potential pathological mechanisms and the feasible treatment approaches for the neurodegenerative and neuropsychiatric disorders caused by T. gondii infection to extend our understanding for pathogenesis and preventive control of toxoplasmosis in humans.
Evidence of compensatory neural hyperactivity in a subgroup of breast cancer survivors treated with chemotherapy and its association with brain aging
Authors: Mulholland Michele M. , Stuifbergen Alexa , De La Torre Schutz Alexa , Franco Rocha Oscar Y. , Blayney Douglas W. , Kesler Shelli R.
Published: December 2024

Introduction

Chemotherapy-related cognitive impairment (CRCI) remains poorly understood in terms of the mechanisms of cognitive decline. Neural hyperactivity has been reported on average in cancer survivors, but it is unclear which patients demonstrate this neurophenotype, limiting precision medicine in this population.

Methods

We evaluated a retrospective sample of 80 breast cancer survivors and 80 non-cancer controls, aged 35–73, for which we had previously identified and validated three data-driven, biological subgroups (biotypes) of CRCI. We measured neural activity using the z-normalized percent amplitude of fluctuation from resting-state functional magnetic resonance imaging (MRI). We tested established, quantitative criteria to determine whether hyperactivity can accurately be considered compensatory. We also calculated the brain age gap by applying a previously validated algorithm to anatomic MRI.

Results

We found that neural activity differed across the three CRCI biotypes and controls (F = 13.5, p < 0.001), with Biotype 2 demonstrating significant hyperactivity compared to the other groups (p < 0.004, corrected), primarily in prefrontal regions. Alternatively, Biotypes 1 and 3 demonstrated significant hypoactivity (p < 0.02, corrected). Hyperactivity in Biotype 2 met several of the criteria to be considered compensatory. However, we also found a positive relationship between neural activity and the brain age gap in these patients (r = 0.45, p = 0.042).

Discussion

Our results indicated that neural hyperactivity is specific to a subgroup of breast cancer survivors and, while it seems to support preserved cognitive function, it could also increase the risk of accelerated brain aging. These findings could inform future neuromodulatory interventions with respect to the risks and benefits of upregulation or downregulation of neural activity.
FacialNet: facial emotion recognition for mental health analysis using UNet segmentation with transfer learning model
Authors: Na In-seop , Aldrees Asma , Hakeem Abeer , Mohaisen Linda , Umer Muhammad , AlHammadi Dina Abdulaziz , Alsubai Shtwai , Innab Nisreen , Ashraf Imran
Published: December 2024

Facial emotion recognition (FER) can serve as a valuable tool for assessing emotional states, which are often linked to mental health. However, mental health encompasses a broad range of factors that go beyond facial expressions. While FER provides insights into certain aspects of emotional well-being, it can be used in conjunction with other assessments to form a more comprehensive understanding of an individual's mental health. This research work proposes a framework for human FER using UNet image segmentation and transfer learning with the EfficientNetB4 model (called FacialNet). The proposed model demonstrates promising results, achieving an accuracy of 90% for six emotion classes (happy, sad, fear, pain, anger, and disgust) and 96.39% for binary classification (happy and sad). The significance of FacialNet is judged by extensive experiments conducted against various machine learning and deep learning models, as well as state-of-the-art previous research works in FER. The significance of FacialNet is further validated using a cross-validation technique, ensuring reliable performance across different data splits. The findings highlight the effectiveness of leveraging UNet image segmentation and EfficientNetB4 transfer learning for accurate and efficient human facial emotion recognition, offering promising avenues for real-world applications in emotion-aware systems and effective computing platforms. Experimental findings reveal that the proposed approach performs substantially better than existing works with an improved accuracy of 96.39% compared to existing 94.26%.
Sex differences in the reactivity of gastric myoelectrical activity and heart rate variability as putative psychophysiological markers in human pain research
Authors: Draganova Rossitza , Hartanto Genisius , Pawlik Robert Jan , Aulenkamp Jana Luisa , Elsenbruch Sigrid
Published: December 2024

Background

This study explored the potential of electrogastrography (EGG) and heart rate variability (HRV) as psychophysiological markers in experimental pain research related to the gut-brain axis. We investigated responses to the experience of pain from the visceral (rectal distension) and somatic (cutaneous heat) pain modalities, with a focus on elucidating sex differences in EGG and HRV responses.

Methods

In a sample of healthy volunteers (29 males, 43 females), EGG and ECG data were collected during a baseline and a pain phase. Data were analyzed for changes in gastric myoelectrical activity and cardiac autonomic regulation, with special attention to sex-specific patterns and correlations with perceptual responses to visceral and somatic pain stimuli, assessed by visual analogue scale ratings.

Results

Acute pain induced significant instability in EGG slow-wave frequency and amplitude, increased tachygastria, and decreased normogastric spectral power, without evidence of sex differences. HRV analyses revealed increases in SDNN, RMSSD, and pNN50 during pain, indicating sympathovagal regulation changes. While there were no significant sex differences in EGG responses, only female participants exhibited significant correlations between visceral pain unpleasantness and EGG alterations. HRV measures, particularly time-domain parameters, showed sex differences, independent of pain-induced autonomic reactivity.

Conclusion

The experience of pain in the lower abdominal region may induce impaired gastric motility. EGG and HRV are sensitive to acute pain and offer insight into pain mechanisms along the gut-brain axis. While EGG responses were consistent across sexes, HRV revealed sex-specific differences, suggesting that autonomic regulation and gastric motility may be modulated differently by pain and psychosocial factors. Further research in patients with chronic visceral pain is warranted.
From behavioral synchrony to language and beyond
Authors: Eulau Katherine , Hirsh-Pasek Kathy
Published: December 2024

Decades of research on joint attention, coordinated joint engagement, and social contingency identify caregiver-child interaction in infancy as a foundation for language. These patterns of early behavioral synchrony contribute to the structure and connectivity of the brain in the temporoparietal regions typically associated with language skills. Thus, children attune to their communication partner and subsequently build cognitive skills directly relating to comprehension and production of language, literacy skills, and beyond. This has yielded marked interest in measuring this contingent, synchronous social behavior neurally. Neurological measures of early social interactions between caregiver and child have become a hotbed for research. In this paper, we review that research and suggest that these early neural couplings between adults and children lay the foundation for a broader cognitive system that includes attention, problem solving, and executive function skills. This review describes the role of behavioral synchrony in language development, asks what the relationship is between neural synchrony and language growth, and how neural synchrony may play a role in the development of a broader cognitive system founded in a socially-gated brain. We address the known neural correlates of these processes with an emphasis on work that examines the tight temporal contingency between communicative partners during these rich social interactions, with a focus on EEG and fNIRS and brief survey of MRI and MEG.
The antitumor mechanisms of glabridin and drug delivery strategies for enhancing its bioavailability
Authors: Li Chong , Wang Yu , Zhang Wenjing , Yang Xiaoman , Wang Yufang , Hou Guanqun , Wang Dongli , Han Bingbing , Zhang Yimin
Published: December 2024

Glabridin, a flavonoid derived from the plant Glycyrrhiza glabra, has garnered significant attention due to its diverse pharmacological effects, including antioxidant, antibacterial, anti-inflammatory, hypolipidemic, and hypoglycemic activities. Studies have shown that glabridin exhibits substantial antitumor activity by modulating the proliferation, apoptosis, metastasis, and invasion of cancer cells through the targeting of various signaling pathways, thus indicating its potential as a therapeutic agent for malignant tumors. To enhance its solubility, stability, and bioavailability, several drug delivery systems have been developed, including liposomes, cyclodextrin inclusion complexes, nanoparticles, and polymeric micelles. These de.livery systems have shown promise in preclinical studies but face challenges in clinical translation, such as issues with biocompatibility, delivery efficiency, and long-term stability. A comprehensive analysis of the antitumor mechanism of glabridin and its novel drug delivery system is still lacking. Therefore, the authors performed a comprehensive review of recent literature on the antitumor effects of glabridin and its novel drug delivery systems, covering the antitumor mechanism, action targets, and novel drug delivery systems, offering new theoretical insights and development directions for its further advancement and clinical application.
Broccoli (Brassica oleracea var. italica) leaves exhibit significant antidiabetic potential in alloxan-induced diabetic rats: the putative role of ABC vacuolar transporter for accumulation of Quercetin and Kaempferol
Authors: Latif Sara , Sameeullah Muhammad , Abbasi Hiffza Qadeer , Masood Zainab , Demiral Sert Tijen , Aslam Noreen , Pekdemir Turgay , Imren Mustafa , Çiftçi Vahdettin , Saba Kiran , Malik Muhammad Suleman , Ijaz Fatima , Batool Neelam , Mirza Bushra , Waheed Mohammad Tahir
Published: December 2024

Background

The global prevalence of diabetes among adults over 18 years of age is expected to increase from 10.5% to 12.2% (between 2021 and 2045). Plants can be a cost-effective source of flavonoids like quercetin and kaempferol with anti-diabetic properties.

Methodology

We aimed to assess the antidiabetic potential of leaves of Brassica oleracea cvs. Green Sprout and Marathon. Further, flavonoid contents were measured in broccoli leaves grown under light and dark conditions. The methanolic extracts of Green Sprout (GSL-M) and Marathon (ML-M) were first evaluated in vitro for their α-amylase and α-glucosidase inhibitory potential and then for antidiabetic activity in vivo in alloxan-induced diabetic rat models.

Results

Treatment with plant extracts promoted the reduced glutathione (GSH) content and CAT, POD, and SOD activities in the pancreas, liver, kidney, heart, and brain of diabetic rats, whereas lowered lipid peroxidation, H2O2, and nitrite concentrations. The histopathological studies revealed the protective effect of plant extracts at high dose (300 mg/kg), which could be due to broccoli’s rich content of chlorogenic acid, quercetin, and kaempferol. Strikingly, etiolated leaves of broccoli manifested higher levels of quercetin and kaempferol than green ones. The putative role of an ABC transporter in the accumulation of quercetin and kaempferol in etiolated leaves was observed as evaluated by qRT-PCR and in silico analyses.

Conclusion

In conclusion, the present study shows a strong link between the antidiabetic potential of broccoli due to the presence of chlorogenic acid, quercetin, and kaempferol and the role of an ABC transporter in their accumulation within the vacuole.
Anti-diabetic therapies on dental implant success in diabetes mellitus: a comprehensive review
Authors: Ghorbani Hamzeh , Minasyan Arsen , Ansari Delaram , Ghorbani Parvin , Wood David A. , Yeremyan Rozi , Ghorbani Simin , Minasian Natali
Published: December 2024

Background and Objective

Dental implant therapy faces challenges in patients with Type 1 and Type 2 Diabetes Mellitus (T1DM and T2DM) due to adverse effects on bone metabolism and immune response. Despite advancements, diabetic patients face higher risks of peri-implantitis and compromised osseointegration. This review assesses the impact of anti-diabetic medications on implant outcomes, offering insights to bridge the gap between animal studies and clinical practice. By evaluating pharmacotherapeutic strategies in preclinical models, this review guides future research designs to improve implant success rates in diabetic individuals.

Method

A comprehensive literature review identified 21 animal studies examining the impact of anti-diabetic medications on dental and bone implants. These studies explored diabetes models, medication regimens, and designs to assess outcomes related to bone metabolism, osseointegration, and peri-implant tissue responses. The findings are systematically summarized, highlighting the scope, design, and procedures of each study. An example includes placing a dental implant in the molar region of a mouse, providing insight into preclinical approaches.

Results

Twenty-one animal studies, primarily using rodents, investigate various anti-diabetic medications on dental and bone implants. Interventions include insulin, aminoguanidine, voglibose, sitagliptin, exenatide, and metformin, analyzing outcomes like bone-implant contact (BIC), bone volume (BV), and counter-torque values in T1DM and T2DM models. The impacts of these medications on implant osseointegration under diabetic conditions are detailed, with their benefits and shortcomings assessed.

Discussion

The findings and challenges of existing animal studies on diabetes mellitus (DM) and implant osseointegration are presented. Despite T2DM prevalence, research primarily focuses on T1DM models due to easier experimental practicalities, limiting applicability. Inconsistent protocols in studies compromise reliability regarding anti-diabetic treatments’ effectiveness on osseointegration. Standardized methodologies and long-term assessments of local drug delivery alongside systemic anti-DM treatments are crucial to manage DM-related complications in implant dentistry.

Conclusion

Insulin administration in short-term T1DM animal studies enhances implant osseointegration. However, the efficacy of non-insulin medications remains inconclusive. Rigorous experimental designs are needed to address inconsistencies and assess long-term impacts. Larger-sized (e.g., porcine) animal studies across various intraoral implant scenarios are required. Future research should focus on enhancing clinical applicability and improving implant stability in evolving conditions.
Forest aboveground biomass estimation based on spaceborne LiDAR combining machine learning model and geostatistical method
Authors: Xu Li , Yu Jinge , Shu Qingtai , Luo Shaolong , Zhou Wenwu , Duan Dandan
Published: December 2024

Estimation of forest biomass at regional scale based on GEDI spaceborne LiDAR data is of great significance for forest quality assessment and carbon cycle. To solve the problem of discontinuous data of GEDI footprints, this study mapped different echo indexes in the footprints to the surface by inverse distance weighted interpolation method, and verified the influence of different number of footprints on the interpolation results. Random forest algorithm was chosen to estimate the spruce-fir biomass combined with the parameters provided by GEDI and 138 spruce-fir sample plots in Shangri-La. The results show that: (1) By extracting different numbers of GEDI footprints and visualize it, the study revealed that a higher number of footprints correlates with a denser distribution and a more pronounced stripe phenomenon. (2) The prediction accuracy improves as the number of GEDI footprints decreases. The group with the highest R2, lowest RMSE and lowest MAE was the footprint extracted every 100 shots, and the footprint extracted every 10 shots had the worst prediction effect. (3) The biomass of spruce-fir inverted by random forest ranged from 51.33 t/hm2 to 179.83 t/hm2, with an average of 101.98 t/hm2. The total value was 3035.29 × 104 t/hm2. This study shows that the number and distribution of GEDI footprints will have a certain impact on the interpolation mapping to the surface information and presents a methodological reference for selecting the appropriate number of GEDI footprints to derive various vertical structure parameters of forest ecosystems.
Genome-wide identification and expression analysis of the cellulose synthase gene family in potato (Solanum tuberosum L.)
Authors: Gong Huiling , Ma Junxian , Dusengemungu Leonce , Feng Zaiping
Published: December 2024

Potato (Solanum tuberosum) is the fourth largest staple food crop globally. However, potato cultivation is frequently challenged by various diseases during planting, significantly impacting both crop quality and yield. Pathogenic microorganisms must first breach the plant’s cell wall to successfully infect potato plants. Cellulose, a polysaccharide carbohydrate, constitutes a significant component of plant cell walls. Within these walls, cellulose synthase (CesA) plays a pivotal role in cellulose synthesis. Despite its importance, studies on StCesAs (the CesA genes in potato) have been limited. In this study, eight CesA genes were identified and designated as StCesA1-8, building upon the previous nomenclature (StCesA1-4). Based on their phylogenetic relationship with Arabidopsis thaliana, these genes were categorized into four clusters (CesA I to CesA IV). The genomic distribution of StCesAs spans seven chromosomes. Gene structure analysis revealed that StCesAs consist of 12 to 14 exons. Notably, the putative promoter regions harbor numerous biologically functional cis-acting regulatory elements, suggesting diverse roles for StCesAs in potato growth and development. RNA-seq data further demonstrated distinct expression patterns of StCesAs across different tissues. Additionally, quantitative real-time PCR (QRT-PCR) results indicated significant up-regulation of StCesA5 expression under biotic stresses, implicating its potential involvement in potato disease resistance.
A new BWO-based RGB vegetation index and ensemble learning strategy for the pests and diseases monitoring of CCB trees using unmanned aerial vehicle
Authors: Hu Keliang , Liu Junchen , Xiao Hai , Zeng Qiangguo , Liu Jun , Zhang Lei , Li Man , Wang Zhihui
Published: December 2024

Introduction

The Cinnamomum Camphora var. Borneol (CCB) tree is a valuable timber species with significant medicinal importance, widely cultivated in mountainous areas but susceptible to pests and diseases, making manual surveillance costly.

Methods

This paper proposes a method for detecting CCB pests and diseases using Unmanned aerial vehicle (UAV) as an advanced data collection carrier, capable of gathering large-scale data. To tackle the high cost and challenging data processing issues associated with traditional hyper-spectral/multi-spectral sensors, this method only relies on UAV visible light RGB bands. The process first involves calculating and normalizing 24 visible light vegetation indices from the UAV RGB images of the monitoring area, along with the original RGB bands. To account for the collinearity relationship between indices, the random forest variable importance and correlation coefficient iterative analysis algorithm are employed to select indices, retaining the most important or lowest collinearity multiple vegetation indices. Subsequently, the Beluga Whale Optimization (BWO) algorithm is utilized to generate a new vegetation index, which is then combined with the multi-threshold segmentation method to propose a BWO-weighted ensemble strategy for obtaining the final pests and diseases detection results.

Results and discussion

The experimental results suggest that the new BWO-based vegetation index has a higher feature expression ability than single indices, and the new BWO-based ensemble strategy can yield more accurate detection results. This approach provides an effective means for low-cost pests and diseases detection of CCB trees.
Automatic screening for posttraumatic stress disorder in early adolescents following the Ya’an earthquake using text mining techniques
Authors: Yuan Yuzhuo , Liu Zhiyuan , Miao Wei , Tian Xuetao
Published: December 2024

Background

Self-narratives about traumatic experiences and symptoms are informative for early identification of potential patients; however, their use in clinical screening is limited. This study aimed to develop an automated screening method that analyzes self-narratives of early adolescent earthquake survivors to screen for PTSD in a timely and effective manner.

Methods

An inquiry-based questionnaire consisting of a series of open-ended questions about trauma history and psychological symptoms, was designed to simulate the clinical structured interviews based on the DSM-5 diagnostic criteria, and was used to collect self-narratives from 430 survivors who experienced the Ya’an earthquake in Sichuan Province, China. Meanwhile, participants completed the PTSD Checklist for DSM-5 (PCL-5). Text classification models were constructed using three supervised learning algorithms (BERT, SVM, and KNN) to identify PTSD symptoms and their corresponding behavioral indicators in each sentence of the self-narratives.

Results

The prediction accuracy for symptom-level classification reached 73.2%, and 67.2% for behavioral indicator classification, with the BERT performing the best.

Conclusions

These findings demonstrate that self-narratives combined with text mining techniques provide a promising approach for automated, rapid, and accurate PTSD screening. Moreover, by conducting screenings in community and school settings, this approach equips clinicians and psychiatrists with evidence of PTSD symptoms and associated behavioral indicators, improving the effectiveness of early detection and treatment planning.
The library is open: a scoping review on queer representation in psychedelic research
Authors: Bartlett Amy , Christ Challian , Martins Bradford , Saxberg Kellen , Ching Terence H. W.
Published: December 2024

The intersection of queer identity and psychedelics has not been thoroughly explored by the research community, historically or in the present day. With growing access to legal psychedelic therapies, it is essential that queer psychedelic experiences are understood sufficiently by clinicians in order to provide the most safe and effective care possible. Psychedelics and queerness are intricately related, and there is strong interest in the use of psychedelics for healing and identity development among queer populations. However, the vast majority of the literature stigmatizes and problematizes queer psychedelic use. Therefore this scoping review seeks to explore the current and historical overlap between psychedelics and queerness in the academic literature. Specifically, this scoping review aims to understand the available academic literatures’ treatment of the meaningful, non-pathologizing use of psychedelics within the queer community, and seeks to highlight the unique potential a queer lens and the queer experience can bring to the study of psychedelics. To do so, we asked what queer psychedelic experiences are reflected in the literature, who is being studied, what queer individuals’ motivations are for using psychedelics, and a review of the impacts of queer psychedelic use discussed in the literature. Literature searches were performed in seven academic databases using a wide breadth of both queer-related and psychedelic-related keywords, which resulted in over thirty thousand resources being captured. After screening, a total of 18 resources were collected as representative of the meaningful overlap of psychedelics and queerness. Based on the findings and research gaps identified, this scoping review makes several recommendations regarding future directions psychedelic researchers and clinicians can pursue to better understand and benefit from the meaningful overlap of psychedelics and queerness. By reclaiming, redefining, and reimagining the meaningful relationship between psychedelics and the queer experience, this review helps move the scientific and clinical conversation into queerer spaces, centering queerness and queer experiences as an essential component of psychedelic research and practice.