Quantification of the fungal pathogen Didymella segeticola in Camellia sinensis using a DNA-based qRT-PCR assay.

The fungal pathogen Didymella segeticola causes leaf spot and leaf blight on tea plant (Camellia sinensis), leading to production losses and affecting tea quality and flavor. Accurate detection and quantification of D. segeticola growth in tea plant leaves are crucial for diagnosing disease severity or evaluating host resistance. In this study, we monitored disease progression and D. segeticola development in tea plant leaves inoculated with a GFP-expressing strain. By contrast, a DNA-based qRT-PCR analysis was employed for a more convenient and maneuverable detection of D. segeticola growth in tea leaves. This method was based on the comparison of D. segeticola-specific DNA encoding a Cys2His2-zinc-finger protein (NCBI accession number: OR987684) in relation to tea plant Cs18S rDNA1. Unlike ITS and TUB2 sequences, this specific DNA was only amplified in D. segeticola isolates, not in other tea plant pathogens. This assay is also applicable for detecting D. segeticola during interactions with various tea cultivars. Among the five cultivars tested, 'Zhongcha102' (ZC102) and 'Fuding-dabaicha' (FDDB) were more susceptible to D. segeticola compared with 'Longjing43' (LJ43), 'Zhongcha108' (ZC108), and 'Zhongcha302' (ZC302). Different D. segeticola isolates also exhibited varying levels of aggressiveness towards LJ43. In conclusion, the DNA-based qRT-PCR analysis is highly sensitive, convenient, and effective method for quantifying D. segeticola growth in tea plant. This technique can be used to diagnose the severity of tea leaf spot and blight or to evaluate tea plant resistance to this pathogen.

Towards building multilingual language model for medicine.

The development of open-source, multilingual medical language models can benefit a wide, linguistically diverse audience from different regions. To promote this domain, we present contributions from the following: First, we construct a multilingual medical corpus, containing approximately 25.5B tokens encompassing 6 main languages, termed as MMedC, enabling auto-regressive domain adaptation for general LLMs; Second, to monitor the development of multilingual medical LLMs, we propose a multilingual medical multi-choice question-answering benchmark with rationale, termed as MMedBench; Third, we have assessed a number of open-source large language models (LLMs) on our benchmark, along with those further auto-regressive trained on MMedC. Our final model, MMed-Llama 3, with only 8B parameters, achieves superior performance compared to all other open-source models on both MMedBench and English benchmarks, even rivaling GPT-4. In conclusion, in this work, We present a large-scale corpus, a benchmark and a series of models to support the development of multilingual medical LLMs.

[Genetic analysis of a child with Dias-Logan syndrome due to variant of BCL11A gene].

OBJECTIVE: To analyze the clinical and genetic characteristics of a child featuring Dias-Logan syndrome. METHODS: A child with speech disorders and delayed psychomotor development from childhood who was admitted to the Rehabilitation Medicine Department of Children's Hospital Affiliated to Zhengzhou University in July 2022 was selected as the research subject. Clinical data of the child was collected. Genomic DNA was extracted from peripheral blood samples of the child and his parents. Potential variant was screened by whole exome sequencing, and candidate variant was verified by Sanger sequencing. RESULTS: The child has presented with global developmental delay, microcephaly, special facial features and behavioral problems. Genetic testing revealed a de novo variant of the BCL11A gene, namely c.561_567delACACGCA (p.Q187fs*7), which was classified as pathogenic (PVS1+PS2+PM2_Supporting). CONCLUSION: The heterozygous variant of BCL11A gene probably underlay the Dias-Logan syndrome in this child. Above finding has enriched the phenotypic and mutational spectrum of the BCL11A gene and provides a basis for genetic counseling and clinical decision-making.

Synthesis of Antifouling Poly(ethylene glycol) Brushes via "Grafting to" Approach for Improved Biodistribution.

Polyethylene glycol (PEG) modification of materials has been identified to mitigate the challenge of biofouling. However, the practical application of PEGylation has been hampered by a low PEGylation density on the material surface. Therefore, developing efficient strategies to promote the PEGylation density is crucial. In this study, PEG brushes (PBs) with various structures were synthesized and their physicochemical properties and biomedical applications were investigated. Compared to benzaldehyde (BA), o-phthalaldehyde (OPA) exhibited higher reactivity with amine groups, resulting in increased grafting density (as high as 96.3%) and improved antifouling properties of PEG brushes. Bottlebrushes fabricated by PEG-OPA and polylysine demonstrated a prolonged circulation time in blood and enhanced potential for magnetic resonance imaging of tumors. Furthermore, the rigidity of the backbone was found to be crucial for the antifouling properties of PEG brushes both in vitro and in vivo. These findings are significant and provide valuable insights into designing biomaterials with superior antifouling performance.

Quantitative Characterization of Zebrafish Caudal Fin Regeneration Based on Mueller Matrix OCT In Vivo.

Zebrafish serves as a valuable model for studying tissue regeneration due to their comprehensive regenerative abilities, particularly in bone tissue. In this study, a Mueller matrix optical coherence tomography (OCT) system was applied to monitor the regenerative processes of zebrafish caudal fins in vivo. The analysis focused on evaluating the thickness of the caudal fin tip and the distribution of internal bone tissue during the regenerative process. Subsequently, the effect of ectoine solution on the regeneration process was observed and discussed. Our findings revealed that the caudal fin blastema did not exhibit phase-induced polarization characteristics in the Mueller matrix OCT images. Statistical analyses indicated that the caudal fins did not fully regenerate to their original state within 21 days. Furthermore, the results suggested that ectoine solution could enhance tissue regeneration. This approach provides a method for quantifying zebrafish caudal fin regeneration and advances observation techniques for biomedical and clinical applications.

[Clinical characteristics and genetic analysis of a child with Char syndrome caused by TFAP2B gene variant].

OBJECTIVE: To explore the clinical features and genetic etiology of a child with Char syndrome. METHODS: A child who was presented at the Department of Child Health, Henan Children's Hospital in February 2022 was selected as the study subject. Clinical data of the child was collected, and peripheral blood samples of the child and her parents were collected for the extraction of genomic DNA. Whole exome sequencing was carried out, and candidate variants were verified by Sanger sequencing and bioinformatic analysis. RESULTS: The child had mainly manifested facial dysmorphism, patent ductus arteriosus, growth retardation, curving of fifth fingers and middle toes. Whole exome sequencing revealed that she has harbored a heterozygous c.944A>C (p.Glu315Ala) variant of the TFAP2B gene, which was verified to be de novo by Sanger sequencing. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the variant was rated to be likely pathogenic (PM1+PM2_Supporting+PM6+PP3). CONCLUSION: The heterozygous c.944A>C (p.Glu315Ala) variant of the TFAP2B gene probably underlay the Char syndrome in this child. Above finding has expanded the mutational and phenotypic spectra of the TFAP2B gene, which has facilitated early identification and diagnosis of Char syndrome.

Effect of Sc spatial distribution on the electronic and ferroelectric properties of AlScN.

While aluminum scandium nitride based ferroelectric materials have shown significant promise for non-volatile memory applications, difficulties relating challenges in device performance, such as electrical leakage, to structural characteristics motivate improved understanding of the fundamental structure-property relationship. Spinodal decomposition has been reported in this material system, consistent with our observation of compositional segregation in AlScN films grown by reactive sputter epitaxy. To better understand the effects of spatially non-uniform Sc concentrations, the electronic and ferroelectric (FE) properties of AlScN as a function of Sc distribution are studied using density functional theory (DFT). We explore the impact of Sc-rich atomic planes in wurtzite AlScN with Sc concentration ranging from 0 to 44 at% through a supercell approach. We find that while spontaneous polarization decreases with Sc concentration (∼133 to 102 µC cm-2), periodic Sc-rich planar clusters slow this effect, suggesting that phase segregation counters the effects of increasing Sc composition. Furthermore, the FE switching barrier per formula unit (f.u.) as a function of composition exhibits a local maximum of 0.60 eV f.u.-1 at 25% Sc concentration in the presence of Sc-rich planes but decreases monotonically (0.51 to 0.28 eV f.u.-1) if Sc is uniformly distributed, suggesting that the spatial distribution of Sc plays an important role in the optoelectronic properties of the material by changing the energy landscape. Sc clustering also decreases the bandgap of the material. This study shows that the structural complexity arising from spatial composition modulation provides tunability of ferroelectric properties in AlScN ferroelectrics.

Obstructive Sleep Apnea Syndrome Exacerbates NASH Progression via Selective Autophagy-Mediated Eepd1 Degradation.

Obstructive sleep apnea syndrome (OSAS), characterized by chronic intermittent hypoxia (CIH), is an independent risk factor for aggravating non-alcoholic steatohepatitis (NASH). The prevailing mouse model employed in CIH research is inadequate for the comprehensive exploration of the impact of CIH on NASH development due to reduced food intake observed in CIH-exposed mice, which deviates from human responses. To address this issue, a pair-feeding investigation with CIH-exposed and normoxia-exposed mice is conducted. It is revealed that CIH exposure aggravates DNA damage, leading to hepatic fibrosis and inflammation. The analysis of genome-wide association study (GWAS) data also discloses the association between Eepd1, a DNA repair enzyme, and OSAS. Furthermore, it is revealed that CIH triggered selective autophagy, leading to the autophagic degradation of Eepd1, thereby exacerbating DNA damage in hepatocytes. Notably, Eepd1 liver-specific knockout mice exhibit aggravated hepatic DNA damage and further progression of NASH. To identify a therapeutic approach for CIH-induced NASH, a drug screening is conducted and it is found that Retigabine dihydrochloride suppresses CIH-mediated Eepd1 degradation, leading to alleviated DNA damage in hepatocytes. These findings imply that targeting CIH-mediated Eepd1 degradation can be an adjunctive approach in the treatment of NASH exacerbated by OSAS.

High Stability and Corrosion-Resistant Gas of Recyclable and Versatile Manganese-Doped Lead-Free Double Perovskite Crystals toward Novel Functional Fabric and Photoelectric Device.

Lead-free halide perovskites possess excellent photoelectric properties, making them widely used in the photoelectric fields. Herein, lead-free double perovskite crystals (PCs) doped with manganese (Cs2NaInCl6:Mn2+) are successfully prepared by the more energy-efficient crystallization method. The crystals emit bright orange-red light under the ultraviolet (UV) lamp, showing unique optical properties. They have the highest photoluminescence quantum yield of 42.91%. The white light-emitting diodes (LEDs) are fabricated using these perovskite crystals, which show a color rendering index of 92 and external quantum efficiency (EQE) as high as 16.3%. Furtherly, perovskite-modified fiber paper made of aramid chopped fibers (ACFs) and polyphenylene sulfide (PPS) exhibited fluorescent properties under different conditions. This paper combines fiber composite technology with PPS fiber filter bags, which are widely used in environmental protection, for the first time and demonstrates functional fiber filter bags with fluorescent characteristics. This filter bag provides an idea for the automatic detection of industrial filtration. Meanwhile, after being exposed to industrial waste gas for 60 h, the filter bag can maintain superior fluorescence performance. In this study, lead-free double perovskites are synthesized using an efficient method for preparing high-performance LEDs and high-stability fluorescent fibers. Concurrently, the application of perovskites in environmental protection is expanded.

Three-dimensional morphological characterization of blood droplets during the dynamic coagulation process.

In this study, we employed a method integrating optical coherence tomography (OCT) with the U-Net and Visual Geometry Group (VGG)-Net frameworks within a convolutional neural network for quantitative characterization of the three dimensional whole blood during the dynamic coagulation process. VGG-Net architecture for the identification of blood droplets across three distinct coagulation stages including drop, gelation, and coagulation achieves an accuracy of up to 99%. In addition, the U-Net architecture demonstrated proficiency in effectively segmenting uncoagulated and coagulated portions of whole blood, as well as the background. Notably, parameters such as volume of uncoagulated and coagulated segments of the whole blood were successfully employed for the precise quantification of the coagulation process, which indicates well for the potential of future clinical diagnostics and analyses.

Predictive Biophysical Neural Network Modeling of a Compendium of in vivo Transcription Factor DNA Binding Profiles for Escherichia coli.

The DNA binding of most Escherichia coli Transcription Factors (TFs) has not been comprehensively mapped, and few have models that can quantitatively predict binding affinity. We report the global mapping of in vivo DNA binding for 139 E. coli TFs using ChIP-Seq. We used these data to train BoltzNet, a novel neural network that predicts TF binding energy from DNA sequence. BoltzNet mirrors a quantitative biophysical model and provides directly interpretable predictions genome-wide at nucleotide resolution. We used BoltzNet to quantitatively design novel binding sites, which we validated with biophysical experiments on purified protein. We have generated models for 125 TFs that provide insight into global features of TF binding, including clustering of sites, the role of accessory bases, the relevance of weak sites, and the background affinity of the genome. Our paper provides new paradigms for studying TF-DNA binding and for the development of biophysically motivated neural networks.

Dyadic coping and associated factors in women with high-risk pregnancy and their spouses: Do they interact?

OBJECTIVE: The objective of this study was to examine the present situation of dyadic coping in pregnant women with high-risk pregnancy and their spouses, as well as the relevant factors and the interactions between partners. METHODS: From October 2022 to September 2023, a cross-sectional survey was undertaken, involving 460 pairs of pregnant women with high-risk pregnancy who were hospitalized for childbirth and their accompanying spouses. These participants completed self-assessments on dyadic coping, marital satisfaction, perceived stress, and self-efficacy through the completion of paper questionnaires. The collected data was then subjected to analysis utilizing correlation analysis and multiple linear regression. The actor-partner interdependence model (APIM) was then developed using the structural equation modeling(SEM) to test the binary association. FINDINGS: Pregnant women preferred to utilize stressful communication, whereas their spouses employed supportive and delegated coping. Both external (such as education level, employment status, and medical insurance) and internal (such as marital satisfaction, perceived stress, and self-efficacy) factors were associated with pregnant women's dyadic coping. Education level and internal factors were also associated with the spouses' dyadic coping. In contrast to spouses, who can only have a partner effect on pregnant women through marriage satisfaction, all pregnant women's internal elements played the partner effect on the spouses' dyadic coping. IMPLICATIONS: The study's findings help identify populations with inadequate coping ability. Promoting marital satisfaction, self-efficacy, and reducing perceived stress are associated with enhancing the dyadic coping ability of pregnant women with high-risk pregnancy and their spouses. It also suggests that antenatal care should intervene with pregnant women with high-risk pregnancy and their spouses as a whole, and emphasize collaborative coping and effective mutual support between couples rather than spousal support alone.

The dyadic associations among self-efficacy, dyadic coping, and health-related quality of life between high-risk pregnant women and spouses: a cross-sectional study.

AIM: Health-related quality of life(HRQoL) is essential for high-risk pregnant women and their spouses. This study aimed to explore the dyadic associations (including actor and partner effects) among self-efficacy, dyadic coping, and HRQoL of high-risk pregnant women and their spouses and examine the mediating effect of dyadic coping. METHODS: This cross-sectional study recruited participants from two Grade A tertiary hospitals in China from October 2022 to September 2023. A questionnaire including the Chinese version of the General Self-Efficacy Scale, Dyadic Coping Inventory, and 12 Short Form Health Survey Scales was used for the survey. The actor-partner interdependence mediation model was constructed to test dyadic associations and mediating effects. RESULTS: In the actor effects, self-efficacy was positively associated with dyadic coping and HRQoL (P < 0.05). Regarding partner effects, pregnant women's self-efficacy was positively associated with spouses' dyadic coping and physical health (P < 0.05). Dyadic coping partially mediated the relationship between self-efficacy and HRQoL for both groups(P < 0.05). CONCLUSION: The HRQoL of high-risk pregnant women and their spouses requires urgent attention. Enhancing self-efficacy and dyadic coping in these couples is related to their improved physical and mental health. Healthcare professionals should consider interactions between couples and include them together in perinatal care. Intervention programs for couples or families based on existing positive psychology and dyadic interventions may work together to improve the HRQoL of couples.

PMC-LLaMA: toward building open-source language models for medicine.

OBJECTIVE: Recently, large language models (LLMs) have showcased remarkable capabilities in natural language understanding. While demonstrating proficiency in everyday conversations and question-answering (QA) situations, these models frequently struggle in domains that require precision, such as medical applications, due to their lack of domain-specific knowledge. In this article, we describe the procedure for building a powerful, open-source language model specifically designed for medicine applications, termed as PMC-LLaMA. MATERIALS AND METHODS: We adapt a general-purpose LLM toward the medical domain, involving data-centric knowledge injection through the integration of 4.8M biomedical academic papers and 30K medical textbooks, as well as comprehensive domain-specific instruction fine-tuning, encompassing medical QA, rationale for reasoning, and conversational dialogues with 202M tokens. RESULTS: While evaluating various public medical QA benchmarks and manual rating, our lightweight PMC-LLaMA, which consists of only 13B parameters, exhibits superior performance, even surpassing ChatGPT. All models, codes, and datasets for instruction tuning will be released to the research community. DISCUSSION: Our contributions are 3-fold: (1) we build up an open-source LLM toward the medical domain. We believe the proposed PMC-LLaMA model can promote further development of foundation models in medicine, serving as a medical trainable basic generative language backbone; (2) we conduct thorough ablation studies to demonstrate the effectiveness of each proposed component, demonstrating how different training data and model scales affect medical LLMs; (3) we contribute a large-scale, comprehensive dataset for instruction tuning. CONCLUSION: In this article, we systematically investigate the process of building up an open-source medical-specific LLM, PMC-LLaMA.

Path Analysis Between Family Functioning and Mental Health in People With Neuropathic Pain: Roles of Pain Intensity, Self-Perceived Burden, Pain Catastrophizing, and Functional Status.

PURPOSE: This study aimed to explore the pathways between family functioning and mental health in people with neuropathic pain, as well as to discuss the mediating role of pain intensity, self-perceived burden, pain catastrophizing, and functional status. DESIGN: Cross-sectional design reported using the STROBE guidelines. METHODS: A total of 277 people with neuropathic pain completed face-to-face questionnaires to evaluate family functioning, pain intensity, pain catastrophizing, self-perceived burden, functional status, and mental health. Structural equation modeling (SEM) was constructed to analyze the pathways between these variables. RESULTS: The positive total effect between family functioning and mental health was significant and partially mediated by self-perceived burden, pain catastrophizing, and functional status. In addition, better family functioning was associated with higher pain intensity, which worsens self-perceived burden, pain catastrophizing, and functional status, masking 23.68% of the positive effects between family functioning and mental health. CONCLUSIONS: Better family functioning was associated with better mental health, as explained by reduced self-perceived burden, reduced pain catastrophizing, and improved functional status. However, this benefit may be partially masked by the relationship that better family functioning explains higher pain intensity. CLINICAL IMPLICATIONS: Nurses' comprehensive assessment and management of neuropathic pain from both the family and individual levels, such as family functioning, pain intensity, self-perceived burden, pain catastrophizing, and functional status, may be beneficial in promoting patients' mental health. In addition, it is necessary to identify why good family functioning is associated with higher pain intensity and intervene in this regard.

Pressure-Insensitive Epidermal Thickness of Fingertip Skin for Optical Image Encryption.

In this study, an internal fingerprint-guided epidermal thickness of fingertip skin is proposed for optical image encryption based on optical coherence tomography (OCT) combined with U-Net architecture of a convolutional neural network (CNN). The epidermal thickness of fingertip skin is calculated by the distance between the upper and lower boundaries of the epidermal layer in cross-sectional optical coherence tomography (OCT) images, which is segmented using CNN, and the internal fingerprint at the epidermis-dermis junction (DEJ) is extracted based on the maximum intensity projection (MIP) algorithm. The experimental results indicate that the internal fingerprint-guided epidermal thickness is insensitive to pressure due to normal correlation coefficients and the encryption process between epidermal thickness maps of fingertip skin under different pressures. In addition, the result of the numerical simulation demonstrates the feasibility and security of the encryption scheme by structural similarity index matrix (SSIM) analysis between the original image and the recovered image with the correct and error keys decryption, respectively. The robustness is analyzed based on the SSIM value in three aspects: different pressures, noise attacks, and data loss. Key randomness is valid by the gray histograms, and the average correlation coefficients of adjacent pixelated values in three directions and the average entropy were calculated. This study suggests that the epidermal thickness of fingertip skin could be seen as important biometric information for information encryption.

Investigation and analysis of magnetic resonance imaging experience and psychological status of patients.

OBJECTIVE: To analyze factors influencing the service experience of magnetic resonance imaging (MRI) examination and psychological status of patients admitted to a hospital and propose targeted solutions, and optimize the examination process and nursing by analyzing the MRI examination experience and psychological effect on patients. METHODS: The MRI examination rooms of two tertiary general hospitals in Haikou City were sampled at random, and 206 patients who met the study criteria were surveyed on site. RESULTS: (1) The item with the lowest mean score for patient examination services was whether earplugs were provided to the patient during the examination (B8 = 0.47). (2) Environmental logistics experience (16.83 ± 3.036) received the lowest score among the three service experience dimensions. (3) The average anxiety score of the patients was 5.38. (4) There was a positive correlation between the examination experience and the examination service experience of the patients. (5) Patients with higher monthly income had decreased anxiety (coefficient = -2.334), and MRI examination of the extremities relieved the anxiety (coefficient = -4.782). CONCLUSION: The environmental logistics factors, poor service attitude, examination site, and income were the most significant factors affecting the MRI examination experience and psychological status of patients, which can be improved by providing information, enhancing the waiting environment, providing targeted patient education, and evaluating the experience immediately.

Federated machine learning in healthcare: A systematic review on clinical applications and technical architecture.

Federated learning (FL) is a distributed machine learning framework that is gaining traction in view of increasing health data privacy protection needs. By conducting a systematic review of FL applications in healthcare, we identify relevant articles in scientific, engineering, and medical journals in English up to August 31st, 2023. Out of a total of 22,693 articles under review, 612 articles are included in the final analysis. The majority of articles are proof-of-concepts studies, and only 5.2% are studies with real-life application of FL. Radiology and internal medicine are the most common specialties involved in FL. FL is robust to a variety of machine learning models and data types, with neural networks and medical imaging being the most common, respectively. We highlight the need to address the barriers to clinical translation and to assess its real-world impact in this new digital data-driven healthcare scene.

Heterozygous CAPZA2 mutations cause global developmental delay, hypotonia with epilepsy: a case report and the literature review.

CAPZA2 encodes the α2 subunit of CAPZA, which is vital for actin polymerization and depolymerization in humans. However, understanding of diseases associated with CAPZA2 remains limited. To date, only three cases have been documented with neurodevelopmental abnormalities such as delayed motor development, speech delay, intellectual disability, hypotonia, and a history of seizures. In this study, we document a patient who exhibited seizures, mild intellectual disability, and impaired motor development yet did not demonstrate speech delay or hypotonia. The patient also suffered from recurrent instances of respiratory infections, gastrointestinal and allergic diseases. A novel de novo splicing variant c.219+1 G > A was detected in the CAPZA2 gene through whole-exome sequencing. This variant led to exon 4 skipping in mRNA splicing, confirmed by RT-PCR and Sanger sequencing. To our knowledge, this is the third study on human CAPZA2 defects, documenting the fourth unambiguously diagnosed case. Furthermore, this splicing mutation type is reported here for the first time. Our research offers additional support for the existence of a CAPZA2-related non-syndromic neurodevelopmental disorder. Our findings augment our understanding of the phenotypic range associated with CAPZA2 deficiency and enrich the knowledge of the mutational spectrum of the CAPZA2 gene.