Search

Two cases of cutaneous angiosarcoma of the scalp and face in the elderly are reported. Case 1 was an 89 years old man with ulcerated edematous, erythematous plagues on the scalp and right face for 2 months. Dermatological examination showed that ulcerated edematous, erythematous patches on the crown, forehead, and right face, with unclear boundaries. The involved skin was tight, shiny, and depressed under pressure. Ulcers and scabs were present on the crown (sized 2 cm×3 cm) and frontotemporal region (sized 4 cm×6 cm). Histopathology showed necrosis and atypical cells arranged in luminal pattern around lesion in the dermis. Immunohistochemistry showed CD31 (+), CD34 (+), ERG (+), HHV8 focal weak positive, P53 mutation, Ki-67 (30% +), CK (-), and CEA (-). Diagnosis: angiosarcoma. The patient and his family refused further diagnosis and treatment, and the patient passed away. Case 2 was an 81 years old female with dark erythema on the right scalp and face for 2 months. Dermatological examination revealed purple patch covered with purple papules and nodules on the right scalp and face. Skin histopathology showed slight thickening of the spinous layers, diffuse proliferation of endothelial cells in the dermis, segmentation of collagen, and atypia. Fissures and vascular lumens containing erythrocytes were also observed in the dermis. Immunohistochemistry: CD31 (+), CD34 (+), D240(+), ERG(+), Ki-67(≈35%+), S100(-), HMB45(-), and CK(-). Diagnosis: angiosarcoma of the scalp and face. The patient was transferred to the oncology department for radiotherapy and chemotherapy, and passed away during follow-up.

Objective: This study aimed to investigate the factors influencing nurses’ ability to respond to public health emergencies and understand the relationship between nurses’ ability to respond to emergencies and workplace resilience. Methods: A cross-sectional study of 361 nurses from military hospitals was conducted from January 18 to September 6, 2022, using an online survey. The Infectious Diseases Emergency Response Capacity (IDERC) questionnaire and the Workplace Resilience Scale (WRS) were utilized, and sociodemographic information was also collected. Data were analyzed using descriptive statistics and frequency analysis. Differences between groups were identified by one-way analysis of variance, and linear regression was used to analyze the main factors influencing the infectious emergency response capacity. Results: The average infectious emergency response capacity score on the IDERC questionnaire and workplace resilience, measured by WRS, were 4.01 (SD = 0.76) and 3.85 (SD = 0.71), respectively, on a scale of 1–5, indicating high performance. Factors such as degree of education, nurses’ service years and experience in epidemic prevention participation were found to be the main influencing factors of the score of IDERC. The level of workplace resilience showed a positive correlation with the capacity to respond to infectious disease, the score of WRS and the service year accounted for 63.6% of the variance in emergency response capabilities. Conclusion: The results indicate an urgent need to strengthen the training of nurses with lower degree of education, shorter service years, no prior work, or no experience of epidemic prevention participation, and hospitals should also prioritize improving nurses’ workplace resilience through targeted interventions, enhancing their abilities in infectious disease prevention, preparation, first aid, and subsequent critical patient care.

Abstract Background The objective was to investigate the efficacy of different doses of levothyroxine therapy among pregnant women exhibiting high-normal thyroid stimulating hormone levels and positive thyroid peroxidase antibodies throughout the first half of pregnancy. Methods Pregnant women exhibiting high-normal thyroid stimulating hormone levels and thyroid peroxidase antibodies positivity throughout the initial half of pregnancy were selected from January 2021 to September 2023. Based on the different doses of levothyroxine, the pregnant women were categorized into the nonintervention group (G0, 122 women), 25 µg levothyroxine intervention group (G25, 69 women), and 50 µg levothyroxine intervention group (G50, 58 women). Serum parameters, gastrointestinal symptoms, small intestinal bacterial overgrowth (SIBO), maternal and neonatal outcomes were compared after the intervention among the three groups. Results After the intervention, in the G25 and G50 groups, the thyroid stimulating hormone, triglyceride and low-density lipoprotein levels were notably less in contrast to those in the G0 group (P

Abstract DANCE is the first standard, generic, and extensible benchmark platform for accessing and evaluating computational methods across the spectrum of benchmark datasets for numerous single-cell analysis tasks. Currently, DANCE supports 3 modules and 8 popular tasks with 32 state-of-art methods on 21 benchmark datasets. People can easily reproduce the results of supported algorithms across major benchmark datasets via minimal efforts, such as using only one command line. In addition, DANCE provides an ecosystem of deep learning architectures and tools for researchers to facilitate their own model development. DANCE is an open-source Python package that welcomes all kinds of contributions.

Bartonella spp. are globally distributed gram-negative facultative intracellular bacteria that infect a wide range of hosts. Rodents are natural reservoirs of many Bartonella species, some of which are also pathogenic to humans. The rapid development of transportation and tourism has highlighted the risk of Bartonella transmission to humans. Thus, it is essential to maintain surveillance of Bartonella spp. infections in rodents. In China, Bartonella spp. infections have been monitored in various areas; however, these have not included the Hulunbuir border regions. In the present study, we monitored the prevalence and genetics of rodent-associated Bartonella spp. in the Hulunbuir border regions. Eleven rodent species were captured at five ports. Eight species were confirmed as Bartonella-positive using quantitative PCR assay, with an overall positivity rate of 20.05 %. Lasiopodomys brandtii was the predominant rodent species captured for Bartonella detection. Sequencing and phylogenetic analysis (using the maximum likelihood method) revealed the presence of three Bartonella species in these rodents, including two pathogenic to humans, namely, Bartonella alsatica and Bartonella grahamii. B. grahamii was the predominant Bartonella species identified in the rodents. Taken together, these results highlight the prevalence and genetic diversity of Bartonella spp. in rodents in the Hulunbuir border regions, indicating the need for risk assessment of human spillover.

GeSn materials with Sn contents ranging between 0% and 11% have been successfully grown by using Ge2H6 and SnCl4 in a hot-wall UHV-CVD system at low reaction pressures of 0.2–0.4 Torr. Both fully strained and partially relaxed materials have been produced. It was found that the materials were of high crystallinity as evidenced by few threading dislocations from cross-sectional TEM. Photoluminescence studies have shown that the PL spectra shift to longer wavelengths, and the PL intensity increases exponentially as the Sn contents increase. The photoemission cutoff for a 9.5% Sn sample is beyond 2600 nm, and low temperature PL measurements have confirmed that this sample is already in the direct gap material regime. Prototype photoconductor devices were fabricated with a partially strained 5% Sn sample, showing much smaller dark currents and similar spectral coverage as compared to a fully strained 7.8% Sn device reported in the literature. The reported technical route has provided a new path toward high quality, low cost GeSn epitaxy, and will contribute to the development of group IV optoelectronics.

Calcium sulfate, generally in the form of gypsum or bassanite, is a significant component in oil well cement. The impact of gypsum/bassanite on the fluid loss of cement slurry was thoroughly examined with varied concentrations of a 2-Acrylamido-2-methylpropane sulfonic acid based fluid loss additive (AMPS-FLA). It was found that bassanite in cement was more conducive to decreasing the fluid loss than gypsum. The results showed that the dissolution rate of bassanite in cement slurry was faster than that of gypsum, generating more Ca2+ and resulting in a reduction in the adsorption capacity of the AMPS-FLA on cement particle surfaces. The adsorption mechanism of FLAs cannot explain the result. This study discovered that the equilibrium concentration of the AMPS-FLA in the pore solution had a good functional relationship with the fluid loss, which was not impacted by cement components. Increasing the equilibrium concentration helped reduce the fluid loss.

ABSTRACT: Avian leukemia virus subgroup J (ALV-J) and chicken infectious anemia virus (CIAV) can be vertically transmitted; however, the pathogenicity of vertically transmitted coinfection with these 2 pathogens has not been studied. In this study, we created a model of chick morbidity in which chicks carried either ALV-J, CIAV, or both viruses via embryo inoculation. Thereafter, we analyzed the effects of vertically transmitted coinfection with CIAV and ALV-J on the pathogenicity of ALV-J and performed a purification assay based on hatching, mortality viremia positivity, and detection of fecal ALV-p27 antigen rates, and body weight. The hatching rate of the ALV-J+CIAV group was 68.57%, lower than those of the single infection and control groups. The survival curve showed that the mortality rates of the CIAV and ALV-J coinfection groups were higher than those of the single infection and control groups. Body weight statistics showed that coinfection aggravated the 7-d growth inhibition effect. The results of ALV-p27 antigen detection in cell culture supernatants showed that the positivity rates of the ALV-J and ALV-J+CIAV groups were 100% at all ages and 0% in the control group. The results of ALV-p27 antigen detection by anal swabs showed that the positivity rates of the ALV-J group were 92.86, 90.90, 88.89, and 93.33% at all ages, and that the ALV-J p27 positivity detection rate of anal swabs was lower than that of plasma virus isolation. The immune organ index of the ALV-J+CIAV group was significantly or very significantly lower than those of the single infection and control groups. The immune organ viral load showed that coinfection with CIAV and ALV-J promoted the proliferation of ALV-J and CIAV in immune organs. Coinfection with ALV-J and CIAV reduced chicken embryo hatchability and increased chick mortality and growth inhibition relative to their respective single infections. Additionally, coinfection with ALV-J + CIAV was even more detrimental in inducing immune organ atrophy (e.g., the thymus, spleen, and bursa), and promoted individual virus replication during coinfection.

ABSTRACT: Marek's disease virus (MDV) is a significant tumorigenic virus that causes severe immunosuppression in chickens. Lentinan (LNT) is an immunomodulator containing β-glucans and is widely used in areas such as antiviral, anticancer, and immune regulation. To investigate the immunomodulatory effects of LNT on specific pathogen-free (SPF) chicks and its potential to inhibit MDV infection, we conducted an MDV challenge experiment and observed the immune-enhancing effect of LNT on SPF chicks. The results showed that LNT promoted the growth and development of SPF chicks and induced the upregulation of cytokines such as Mx protein, interferon-γ (INF-γ), tumor necrosis factor-α (TNF-α), and interleukin-2 (IL-2). The specific gravity of CD4+ T-lymphocytes and CD8+ T-lymphocytes and their ratios were also significantly upregulated. Prophylactic use of LNT inhibited MDV replication in lymphocytes, liver, and spleen. It also alleviated MDV-induced weight loss and hepatosplenomegaly in SPF chicks. The present study confirms that LNT can enhance the levels of innate and cellular immunity in SPF chicks and contributes to the inhibition of MDV replication in vivo and mitigation of immune organ damage in chicks due to MDV infection. This provides an adjunctive measure for better control of MDV infection.

Background Although several studies have addressed plasma proteomics in heart failure with preserved ejection fraction, limited data are available on the prognostic value of urinary proteomics. The objective of our study was to identify urinary proteins/peptides associated with death and heart failure admission in patients with heart failure with preserved ejection fraction. Methods and Results The study population included participants enrolled in TOPCAT (Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist Trial). The relationship between urine protein levels and the risk of death or heart failure admission was assessed using Cox regression, in both nonadjusted analyses and adjusting for urine creatinine levels, and the MAGGIC (Meta‐Analysis Global Group in Chronic Heart Failure) score. A total of 426 (12.4%) TOPCAT participants had urinary protein data and were included. There were 40 urinary proteins/peptides significantly associated with death or heart failure admission in nonadjusted analyses, 21 of which were also significant adjusted analyses. Top proteins in the adjusted analysis included ANGPTL2 (angiopoietin‐like protein 2) (hazard ratio [HR], 0.5731 [95% CI, 0.47–0.7]; P=3.13E‐05), AMY2A (α amylase 2A) (HR, 0.5496 [95% CI, 0.44–0.69]; P=0.0001), and DNASE1 (deoxyribonuclease‐1) (HR, 0.5704 [95% CI, 0.46–0.71]; P=0.0002). Higher urinary levels of proteins involved in fibrosis (collagen VI α‐1, collagen XV α‐1), metabolism (pancreatic α‐amylase 2A/B, mannosidase α class 1A member 1), and inflammation (heat shock protein family D member 1, inducible T cell costimulatory ligand) were associated with a lower risk of death or heart failure admission. Conclusions Our study identifies several novel associations between urinary proteins/peptides and outcomes in heart failure with preserved ejection fraction. Many of these associations are independent of clinical risk scores and may aid in risk stratification in this patient population.

BackgroundHospital resilience is essential in responding to disasters, but current research focuses mainly on frameworks and models rather than the protection of resilience and analysis of risk factors during public health emergencies. This study aims to examine the development of resilience in Chinese frontline hospitals during the initial COVID-19 outbreak in 2020, providing insights for future disaster response efforts.ObjectivesWe conducted interviews with 26 hospital staff members who were involved in the initial response to the COVID-19 outbreak in China. We used a semi-structured interview approach and employed purposive sampling and snowball sampling techniques. The interview outline was guided by the ‘Action Framework’ proposed by the World Health Organization (WHO) for responding to infectious disease emergencies. This framework includes dimensions such as command, surveillance, risk communication, medical response, and public health response. We analyzed the collected data using Colaizzi’s seven-step data analysis method and the template analysis method.ResultsWHO’s ‘action framework’ effectively highlights the factors that contribute to hospital resilience. While medical response, including the availability of materials and facilities, the use of information technology, and the capacity for infectious disease diagnosis and treatment, remains crucial, other important aspects include awareness and beliefs about infections, treatment experience, interdisciplinary collaboration, and more. Additionally, it is essential to establish an intelligent command system, foster trusting partnerships between teams, improve monitoring capabilities for infectious disease agents, enhance risk communication through information synchronization and transparency, strengthen infection control planning, and improve environmental disinfection capabilities for effective public health emergency response. These contradictions significantly impact the enhancement of hospital resilience in dealing with major infectious disease outbreaks.ConclusionIn responding to sudden major infectious diseases, hospitals play a vital role within the healthcare system. Enhancing hospital resilience involves more than just improving treatment capabilities. It also requires effective command coordination at the hospital level, infection control planning, and the deployment of intelligent equipment. Additionally, planning for effective communication and coordination between hospitals, communities, and the national healthcare system can further enhance hospital resilience.

Abstract The rapidly evolving landscape of biomarkers for colorectal cancer (CRC) necessitates an integrative, updated repository. In response, we constructed the Colorectal Cancer Biomarker Database (CBD), which collected and displayed the curated biomedicine information for 870 CRC biomarkers in the previous study. Building on CBD, we have now developed CBD2, which includes information on 1569 newly reported biomarkers derived from different biological sources (DNA, RNA, protein, and others) and clinical applications (diagnosis, treatment, and prognosis). CBD2 also incorporates information on nonbiomarkers that have been identified as unsuitable for use as biomarkers in CRC. A key new feature of CBD2 is its network analysis function, by which users can investigate the visible and topological network between biomarkers and identify their relevant pathways. CBD2 also allows users to query a series of chemicals, drug combinations, or multiple targets, to enable multidrug, multitarget, multipathway analyses, toward facilitating the design of polypharmacological treatments for CRC. CBD2 is freely available at http://www.eyeseeworld.com/cbd.

Breast cancer continues to have a high incidence rate among female malignancies. Despite significant advancements in treatment modalities, the heterogeneous nature of breast cancer and its resistance to various therapeutic approaches pose considerable challenges. Antibody-drug conjugates (ADCs) effectively merge the specificity of antibodies with the cytotoxicity of chemotherapeutic agents, offering a novel strategy for precision treatment of breast cancer. Notably, trastuzumab emtansine (T-DM1) has provided a new therapeutic option for HER2-positive breast cancer patients globally, especially those resistant to conventional treatments. The development of trastuzumab deruxtecan (T-DXd) and sacituzumab govitecan (SG) has further broadened the applicability of ADCs in breast cancer therapy, presenting new hopes for patients with low HER2 expression and triple-negative breast cancer. However, the application of ADCs presents certain challenges. For instance, their treatment may lead to adverse reactions such as interstitial lung disease, thrombocytopenia, and diarrhea. Moreover, prolonged treatment could result in ADCs resistance, complicating the therapeutic process. Economically, the high costs of ADCs might hinder their accessibility in low-income regions. This article reviews the structure, mechanism of action, and clinical trials of commercially available ADCs for breast cancer treatment, with a focus on the clinical trials of the three drugs, aiming to provide insights for clinical applications and future research.

An efficient obstacle detection system is one of the most important guarantees for improving the active safety performance of autonomous vehicles. This paper proposes an obstacle detection method based on high-precision positioning applied to blocked zones to solve the problems of the high complexity of detection results, low computational efficiency, and high load in traditional obstacle detection methods. Firstly, an NDT registration method which uses the likelihood function as the optimal value of the registration score function to calculate the registration parameters is designed to match the scanning point cloud and the target point cloud. Secondly, a target reduction method combined with threshold judgment and the binary tree search algorithm is designed to filter the point cloud of non-road obstacles to improve the processing speed of the computing platform. Meanwhile, KD-tree is used to speed up the clustering process. Finally, a vehicle remote control simulation platform with the combination of a cloud platform and mobile terminal is designed to verify the effectiveness of the strategy in practical application. The results prove that the proposed obstacle detection method can improve the efficiency and accuracy of detection.

This study systematically investigates the impact of pre-stretching amount (PSA) on the acceleration, motion status, and screening efficiency of the Flip-flow screen plate (FFSP). Initially, a nonlinear spring-multi-body model of the FFSP is established. Subsequently, the acceleration signals at the midpoint of the FFSP under various PSAs are measured and analyzed. The nonlinear stiffness coefficient of FFSP along the vertical direction is then determined and it is found that simplifying the nonlinear spring-multi-body system to a nonlinear spring-tri-body system under the experimental conditions can maintain the calculation error of FFSP’s acceleration within 30%. Phase and Poincaré mapping diagrams of the FFSP under different PSAs are subsequently created to illustrate the impact of PSA on the motion status of the FFSP. Finally, screening experiments are performed to study the optimal PSA for a kind of bituminous coal from Shanxi province.

Pepper (Capsicum annuum L.) is a herbaceous plant species in the family Solanaceae. Capsicum anthracnose is caused by the genus Colletotrichum. spp., which decreases pepper production by about 50% each year due to anthracnose. In this study, we evaluated the resistance of red ripe fruits from 17 pepper varieties against anthracnose fungus Colletotrichum capsici. We assessed the size of the lesion diameter and conducted significance analysis to identify the resistant variety of B158 and susceptible variety of B161. We selected a resistant cultivar B158 and a susceptible cultivar B161 of pepper and used a transcription to investigate the molecular mechanisms underlying the plant’s resistance to C. capsici, of which little is known. The inoculated fruit from these two varieties were used for the comparative transcription analysis, which revealed the anthracnose-induced differential transcription in the resistant and susceptible pepper samples. In the environment of an anthrax infection, we found that there were more differentially expressed genes in resistant varieties compared to susceptible varieties. Moreover, the response to stimulus and stress ability was stronger in the KANG. The transcription analysis revealed the activation of plant hormone signaling pathways, phenylpropanoid synthesis, and metabolic processes in the defense response of peppers against anthracnose. In addition, ARR-B, AP2-EREBP, bHLH, WRKY, and NAC are associated with disease resistance to anthracnose. Notably, WRKY and NAC were found to have a potentially positive regulatory role in the defense response against anthracnose. These findings contribute to a more comprehensive understanding of the resistance mechanisms of red pepper fruit to anthracnose infection, providing valuable molecular insights for further research on the resistance mechanisms and genetic regulations during this developmental stage of pepper.

Single-cell technologies are revolutionizing the entire field of biology. The large volumes of data generated by single-cell technologies are high dimensional, sparse, and heterogeneous and have complicated dependency structures, making analyses using conventional machine learning approaches challenging and impractical. In tackling these challenges, deep learning often demonstrates superior performance compared to traditional machine learning methods. In this work, we give a comprehensive survey on deep learning in single-cell analysis. We first introduce background on single-cell technologies and their development, as well as fundamental concepts of deep learning including the most popular deep architectures. We present an overview of the single-cell analytic pipeline pursued in research applications while noting divergences due to data sources or specific applications. We then review seven popular tasks spanning different stages of the single-cell analysis pipeline, including multimodal integration, imputation, clustering, spatial domain identification, cell-type deconvolution, cell segmentation, and cell-type annotation. Under each task, we describe the most recent developments in classical and deep learning methods and discuss their advantages and disadvantages. Deep learning tools and benchmark datasets are also summarized for each task. Finally, we discuss the future directions and the most recent challenges. This survey will serve as a reference for biologists and computer scientists, encouraging collaborations. [ABSTRACT FROM AUTHOR]