The global patent landscape of emerging infectious disease monkeypox.

BACKGROUND: Monkeypox is an emerging infectious disease with confirmed cases and deaths in several parts of the world. In light of this crisis, this study aims to analyze the global knowledge pattern of monkeypox-related patents and explore current trends and future technical directions in the medical development of monkeypox to inform research and policy. METHODS: A comprehensive study of 1,791 monkeypox-related patents worldwide was conducted using the Derwent patent database by descriptive statistics, social network method and linear regression analysis. RESULTS: Since the 21st century, the number of monkeypox-related patents has increased rapidly, accompanied by increases in collaboration between commercial and academic patentees. Enterprises contributed the most in patent quantity, whereas the initial milestone patent was filed by academia. The core developments of technology related to the monkeypox include biological and chemical medicine. The innovations of vaccines and virus testing lack sufficient patent support in portfolios. CONCLUSIONS: Monkeypox-related therapeutic innovation is geographically limited with strong international intellectual property right barriers though it has increased rapidly in recent years. The transparent licensing of patent knowledge is driven by the merger and acquisition model, and the venture capital, intellectual property and contract research organization model. Currently, the patent thicket phenomenon in the monkeypox field may slow the progress of efforts to combat monkeypox. Enterprises should pay more attention to the sharing of technical knowledge, make full use of drug repurposing strategies, and promote innovation of monkeypox-related technology in hotspots of antivirals (such as tecovirimat, cidofovir, brincidofovir), vaccines (JYNNEOS, ACAM2000), herbal medicine and gene therapy.

Intrarelationships between suboptimal health status and anxiety symptoms: A network analysis.

BACKGROUND: Suboptimal health status is a global public health concern of worldwide academic interest, which is an intermediate health status between health and illness. The purpose of the survey is to investigate the relationship between anxiety statuses and suboptimal health status and to identify the central symptoms and bridge symptoms. METHODS: This study recruited 26,010 participants aged <60 from a cross-sectional study in China in 2022. General Anxiety Disorder-7 (GAD-7) and suboptimal health status short form (SHSQ-9) were used to quantify the levels of anxiety and suboptimal health symptoms, respectively. The network analysis method by the R program was used to judge the central and bridge symptoms. The Network Comparison Test (NCT) was used to investigate the network differences by gender, place of residence, and age in the population. RESULTS: In this survey, the prevalence of anxiety symptoms, SHS, and comorbidities was 50.7 %, 54.8 %, and 38.5 %, respectively. "Decreased responsiveness", "Shortness of breath", "Uncontrollable worry" were the nodes with the highest expected influence. "Irritable", "Exhausted" were the two symptom nodes with the highest expected bridge influence in the network. There were significant differences in network structure among different subgroup networks. LIMITATIONS: Unable to study the causal relationship and dynamic changes among variables. Anxiety and sub-health were self-rated and may be limited by memory bias. CONCLUSIONS: Interventions targeting central symptoms and bridge nodes may be expected to improve suboptimal health status and anxiety in Chinese residents. Researchers can build symptom networks for different populations to capture symptom relationships.

A conformal regressor for predicting negative conversion time of Omicron patients.

In light of the situation and the characteristics of Omicron, the country has continuously optimized the rules for the prevention and control of COVID-19. The global epidemic is still spreading, and new cases of infection continue to emerge in China. To facilitate the infected person to estimate the course of virus infection, a prediction model for predicting negative conversion time is proposed in this article. The clinical features of Omicron-infected patients in Shandong Province in the first half of 2022 are retrospectively studied. These features are grouped by disease diagnosis result, clinical sign, traditional Chinese medicine symptoms, and drug use. These features are input to the eXtreme Gradient Boosting (XGBoost) model, and the output is the predicted number of negative conversion days. At the same time, XGBoost is used as the underlying algorithm of the conformal prediction (CP) framework, which can realize the probability interval estimation with a controllable error rate. The results show that the proposed model has a mean absolute error of 3.54 days and has the shortest interval prediction result. This shows that the method in this paper can carry more decision-making information and help people better understand the disease and self-estimate the course of the disease to a certain extent.

MM-SFENet: multi-scale multi-task localization and classification of bladder cancer in MRI with spatial feature encoder network.

Objective. Bladder cancer is a common malignant urinary carcinoma, with muscle-invasive and non-muscle-invasive as its two major subtypes. This paper aims to achieve automated bladder cancer invasiveness localization and classification based on MRI.Approach. Different from previous efforts that segment bladder wall and tumor, we propose a novel end-to-end multi-scale multi-task spatial feature encoder network (MM-SFENet) for locating and classifying bladder cancer, according to the classification criteria of the spatial relationship between the tumor and bladder wall. First, we built a backbone with residual blocks to distinguish bladder wall and tumor; then, a spatial feature encoder is designed to encode the multi-level features of the backbone to learn the criteria.Main Results. We substitute Smooth-L1 Loss with IoU Loss for multi-task learning, to improve the accuracy of the classification task. By learning two datasets collected from bladder cancer patients at the hospital, the mAP, IoU, Acc, Sen and Spec are used as the evaluation metrics. The experimental result could reach 93.34%, 83.16%, 85.65%, 81.51%, 89.23% on test set1 and 80.21%, 75.43%, 79.52%, 71.87%, 77.86% on test set2.Significance. The experimental result demonstrates the effectiveness of the proposed MM-SFENet on the localization and classification of bladder cancer. It may provide an effective supplementary diagnosis method for bladder cancer staging.

Effects of Natural Products on Enzymes Involved in Ferroptosis: Regulation and Implications.

Ferroptosis is a form of regulated cell death that is characterized by the accumulation of iron-dependent lipid peroxides. The regulation of ferroptosis involves both non-enzymatic reactions and enzymatic mechanisms. Natural products have demonstrated potential effects on various enzymes, including GPX4, HO-1, NQO1, NOX4, GCLC, and GCLM, which are mainly involved in glutathione metabolic pathway or oxidative stress regulation, and ACSL3 and ACSL4, which mainly participate in lipid metabolism, thereby influencing the regulation of ferroptosis. In this review, we have provided a comprehensive overview of the existing literature pertaining to the effects of natural products on enzymes involved in ferroptosis and discussed their potential implications for the prevention and treatment of ferroptosis-related diseases. We also highlight the potential challenge that the majority of research has concentrated on investigating the impact of natural products on the expression of enzymes involving ferroptosis while limited attention is given to the regulation of enzyme activity. This observation underscores the considerable potential and scope for exploring the influence of natural products on enzyme activity.

Aberrant intrinsic functional brain topology in methamphetamine-dependent individuals after six-months of abstinence.

Our aim was to explore the aberrant intrinsic functional topology in methamphetamine-dependent individuals after six months of abstinence using resting-state functional magnetic imaging (rs-fMRI). Eleven methamphetamines (MA) abstainers who have abstained for six months and eleven healthy controls (HC) were recruited for rs-fMRI examination. The graph theory and functional connectivity (FC) analysis were employed to investigate the aberrant intrinsic functional brain topology between the two groups at multiple levels. Compared with the HC group, the characteristic shortest path length ($ {L}_{p} $) showed a significant decrease at the global level, while the global efficiency ($ {E}_{glob} $) and local efficiency ($ {E}_{loc} $) showed an increase considerably. After FDR correction, we found significant group differences in nodal degree and nodal efficiency at the regional level in the ventral attentional network (VAN), dorsal attentional network (DAN), somatosensory network (SMN), visual network (VN) and default mode network (DMN). In addition, the NBS method presented the aberrations in edge-based FC, including frontoparietal network (FPN), subcortical network (SCN), VAN, DAN, SMN, VN and DMN. Moreover, the FC of large-scale functional brain networks revealed a decrease within the VN and SCN and between the networks. These findings suggest that some functions, e.g., visual processing skills, object recognition and memory, may not fully recover after six months of withdrawal. This leads to the possibility of relapse behavior when confronted with MA-related cues, which may contribute to explaining the relapse mechanism. We also provide an imaging basis for revealing the neural mechanism of MA-dependency after six months of abstinence.

Identification of critical SARS-CoV-2 amino acids associated with COVID-19 hospitalization rate using machine learning and statistical modeling: An observational study in the United States.

BACKGROUND: The COVID-19 pandemic has put many medical systems on the verge of collapse in the last two years. Virus mutation was one of the important factors affecting the COVID-19 infection severity and hospitalizations. Although over ten thousand SARS-CoV-2 mutations being reported since the beginning of the COVID-19 pandemic, only a small percentage of mutations are likely to affect the virus phenotype and change its severity. Finding out which amino acids have the greatest impact on COVID-19 hospitalization rate is an important research question. METHODS: This observational study used the COVID-19 case hospitalization ratio (CHR) to represent the virus severity related with hospitalization. The database is based on the daily state-level epidemiological and genomic sequential data in the United States from the Alpha wave to the first Omicron wave. The critical amino acids that mostly affected the CHR were determined by using four types of models including extreme gradient boosting decision trees (XGBoost), artificial neural networks (ANNs), logistic regression and Lasso regression models. RESULTS: The XGBoost, ANN, logistic regression, and Lasso regression models all produce excellent results (mean square error for all state-level models does not exceed 0.0008 using the testing dataset). Based on the rank of importance of all covariates, the critical amino acids most affecting the CHR were identified, including T19, L24, P25, P26, A27, A67, H69, V70, T95, G142, V143, Y145, E156, F157, N211, L212, V213, R214, D215, G339, R346, S373, L452, S477, T478, E484, N501, A570, P681, and T716. CONCLUSION: This study identified critical amino acids that are most likely to affect the hospitalization rate, allowing public health workers to monitor these highly risky amino acids and raise an alarm immediately when more severe mutations occur. Furthermore, the methodology and results may be extended to other regions.

SAMS-Net: Fusion of attention mechanism and multi-scale features network for tumor infiltrating lymphocytes segmentation.

Automatic segmentation of tumor-infiltrating lymphocytes (TILs) from pathological images is essential for the prognosis and treatment of cancer. Deep learning technology has achieved great success in the segmentation task. It is still a challenge to realize accurate segmentation of TILs due to the phenomenon of blurred edges and adhesion of cells. To alleviate these problems, a squeeze-and-attention and multi-scale feature fusion network (SAMS-Net) based on codec structure, namely SAMS-Net, is proposed for the segmentation of TILs. Specifically, SAMS-Net utilizes the squeeze-and-attention module with the residual structure to fuse local and global context features and boost the spatial relevance of TILs images. Besides, a multi-scale feature fusion module is designed to capture TILs with large size differences by combining context information. The residual structure module integrates feature maps from different resolutions to strengthen the spatial resolution and offset the loss of spatial details. SAMS-Net is evaluated on the public TILs dataset and achieved dice similarity coefficient (DSC) of 87.2% and Intersection of Union (IoU) of 77.5%, which improved by 2.5% and 3.8% compared with UNet. These results demonstrate the great potential of SAMS-Net in TILs analysis and can further provide important evidence for the prognosis and treatment of cancer.

What, Where, When and How of COVID-19 Patents Landscape: A Bibliometrics Review.

Two years after COVID-19 came into being, many technologies have been developed to bring highly promising bedside methods to help fight this epidemic disease. However, owing to viral mutation, how far the promise can be realized remains unclear. Patents might act as an additional source of information for informing research and policy and anticipating important future technology developments. A comprehensive study of 3741 COVID-19-related patents (3,543 patent families) worldwide was conducted using the Derwent Innovation database. Descriptive statistics and social network analysis were used in the patent landscape. The number of COVID-19 applications, especially those related to treatment and prevention, continued to rise, accompanied by increases in governmental and academic patent assignees. Although China dominated COVID-19 technologies, this position is worth discussing, especially in terms of the outstanding role of India and the US in the assignee collaboration network as well as the outstanding invention portfolio in Italy. Intellectual property barriers and racist treatment were reduced, as reflected by individual partnerships, transparent commercial licensing and diversified portfolios. Critical technological issues are personalized immunity, traditional Chinese medicine, epidemic prediction, artificial intelligence tools, and nucleic acid detection. Notable challenges include balancing commercial competition and humanitarian interests. The results provide a significant reference for decision-making by researchers, clinicians, policymakers, and investors with an interest in COVID-19 control.

The global mRNA vaccine patent landscape.

In light of their quick development and low risk, mRNA vaccines are gradually replacing traditional vaccines. In order to characterize the patent landscape of mRNA vaccines, this study collated mRNA vaccine-related applications that have been registered since 1962. Accordingly, the 1852 patent families were discussed in relation to their temporal distribution, geographic scope, organizational assignees, and co-patenting activities. mRNA vaccines were shown to demonstrate promise in infectious disease, cancer immunotherapy, and allergic disease, with a focus on lipid nanoparticles. Notably, these vaccines are being developed against a backdrop of fierce industrial competition and intensive collaboration with a rise in applications. The findings of this study highlighted cutting-edge inventions, key players, and collaboration dynamics among institutions. By understanding the landscape of mRNA vaccine patents, researchers and those in industry may better comprehend the latest trends in this area, which may also assist relevant decision-making by academics, government officials, and industrial leaders.

The Changing Global Landscape in the Development of Artemisinin-Based Treatments: A Clinical Trial Perspective.

Artemisinin and its derivatives (ARTs), due to their potent antimalarial activities, are widely used as frontline antimalarials across the world. Although the large-scale deployment of ARTs has significantly contributed to a substantial decline in malaria deaths, the global malaria burden is still high. New antimalarial treatments need to be developed to manage the growing artemisinin resistance. Understanding the status of ART development is crucial for developing strategies for new alternatives and identifying opportunities to develop ART-based treatments. This study sampled ART clinical trials from the past two decades to gain an overview of the global ART-development landscape. A total of 768 trials were collected to analyze the disease focuses, activity trends, development status, geographic distribution, and combination treatment profiles of ART trials. The findings highlighted the constant focus of ARTs on malaria, the evolving combination research focus, the distinctions between ART development preferences across global regions, the urgent demands for treatments for artemisinin-resistant malaria, and the unavoidable need to consider ART combinations in the development of new antimalarials.

Global Patent Landscape of Benign Prostatic Hyperplasia Drugs.

OBJECTIVE: To characterize the changing landscape of BPH drugs by investigating patent documents derived from pipeline projects. Benign prostatic hyperplasia (BPH) drugs were first approved for the mainstream market about 20 years ago. The fixed patent term warns of possibly transforming the landscape of BPH drugs as technological and commercial substitution causes the displacement of established technologies and competitors by newer ones. However, very few studies focus on patents of BPH drugs, though many literature reviews have analyzed this topic from technological and clinical perspectives. METHODS: All available patent data relevant to BPH-related drugs were collected from the Cortellis database. Descriptive statistics, bibliometric analyses, and citation analyses were used to analyze the patent landscape. RESULTS: By analyzing 1,936 patent families from 1967 to 2019, this study addresses the main results on the changing landscape of BPH drugs, involving associated indications, the shifting centers of innovation globally, notable formulation patents, and promising therapeutics. CONCLUSION: The results provide a significant reference for decision-making by researchers, clinicians, policymakers, and investors with an interest in BPH drugs.

A comprehensive quality analysis of randomized controlled clinical trials of Asian ginseng and American ginseng based on the CONSORT guideline.

Ginseng is an international herb that has been used for thousands of years. Two species most commonly applied and investigated in the ginseng family are Asian ginseng and American ginseng. The number of randomized controlled clinical trials (RCTs) has conspicuously increased, driven by the rapid development of ginseng. However, the reporting of RCT items of ginseng is deficient because of different trial designs and reporting formats, which is a challenge for researchers who are looking for the data with high quality and reliability. Thus, this study focused on providing an extensive analysis of these two species and examined the quality of the RCTs, based on the Consolidated Standards of Reporting Trials (CONSORT) guideline. Ninety-one RCTs conducted from 1980 to 2019 that were related to Asian ginseng and American ginseng used singly met our inclusion criteria. We found that the reporting quality of the two species has improved during the past 40 years. Publication date and sample size were significantly associated with the reporting quality. Rigorous RCTs designed for the species of ginseng are warranted, which can shed light on product research and development of ginseng in the future.

Effect of perioperative nursing for artificial knee replacement on patients with osteosarcoma of the distal femur.

OBJECTIVE: To investigate the clinical application of perioperative nursing care for patients with osteosarcoma of the distal femur who received artificial knee replacement. METHODS: A total of 80 patients with osteosarcoma of the distal femur admitted to our hospital from March 2019 to March 2020 were selected as research subjects and divided into the control group and the study group according to their admission sequence. The control group was given routine nursing care, while the study group was given perioperative nursing care. The negative emotions, sleep quality, limb function, pain, complication rate, and nursing satisfaction of the two groups of patients after nursing care were analyzed. RESULTS: After nursing care, (1) the Hamilton depression rating scale (HAMD) and Hamilton anxiety scale (HAMA) scores of the study group were both lower than those of the control group; (2) the sleep quality score of the study group was lower than that of the control group (P < 0.001); (3) the study group obtained higher limb function score and excellent-and-good rate than the control group (P < 0.05); (4) the pain score of the study group was lower than that of the control group (P < 0.05), and the time to functional exercise and length of hospital stay of the study group were shorter than those of the control group (P < 0.05); (5) patients in the study group had a lower complication rate than those in the control group (P=0.02); (6) the nursing satisfaction rating of the study group was higher than that of the control group (P < 0.001). CONCLUSION: For patients with osteosarcoma of the distal femur treated by artificial knee replacement, in addition to the amelioration of negative emotions and sleep quality, perioperative nursing also improves the patients' limb function and satisfaction and mitigates pain and complications.

Litchi (Litchi chinensis Sonn.): a comprehensive review of phytochemistry, medicinal properties, and product development.

Since ancient times, litchi has been well recognized as a functional food for the management of various ailments. Many bioactives, including flavanoids, anthocyanins, phenolics, sesquiterpenes, triterpenes, and lignans, have been identified from litchi with a myriad of biological properties both in vitro and in vivo. In spite of the extensive research progress, systemic reviews regarding the bioactives of litchi are rather scarce. Therefore, it is crucial to comprehensively analyze the pharmacological activities and the structure-activity relationships of the abundant bioactives of litchi. Besides, more and more studies have focused on litchi preservation and development of its by-products, which is significant for enhancing the economic value of litchi. Based on the analysis of published articles and patents, this review aims to reveal the development trends of litchi in the healthcare field by providing a systematic summary of the pharmacological activities of its extracts, its phytochemical composition, and the nutritional and potential health benefits of litchi seed, pulp and pericarp with structure-activity relationship analysis. In addition, its by-products also exhibited promising development potential in the field of material science and environmental protection. Furthermore, this study also provides an overview of the strategies of the postharvest storage and processing of litchi.

Global landscape of patents related to human coronaviruses.

At present, the COVID-19 pandemic is running rampant, having caused 2.18 million deaths. Characterizing the global patent landscape of coronaviruses is essential not only for informing research and policy, given the current pandemic crisis, but also for anticipating important future developments. While patents are a promising indicator of technological knowledge production widely used in innovation research, they are often an underused resource in biological sciences. In this study, we present a patent landscape for the seven coronaviruses known to infect humans. The information included in this paper provides a strong intellectual groundwork for the ongoing development of therapeutic agents and vaccines along with a deeper discussion of intellectual property rights under epidemic conditions. The results show that there has been a rapid increase in human coronavirus patents, especially COVID-19 patents. China and the United States play an outstanding role in global cooperation and patent application. The leading role of academic institutions and government is increasingly apparent. Notable technological issues related to human coronaviruses include pharmacochemical treatment, diagnosis of viral infection, viral-vector vaccines, and traditional Chinese medicine. Furthermore, a critical challenge lies in balancing commercial competition, enterprise profit, knowledge sharing, and public interest.

ChemGenerator: a web server for generating potential ligands for specific targets.

In drug discovery, one of the most important tasks is to find novel and biologically active molecules. Given that only a tip of iceberg of drugs was founded in nearly one-century's experimental exploration, it shows great significance to use in silico methods to expand chemical database and profile drug-target linkages. In this study, a web server named ChemGenerator was proposed to generate novel activates for specific targets based on users' input. The ChemGenerator relies on an autoencoder-based algorithm of Recurrent Neural Networks with Long Short-Term Memory by training of 7 million of molecular Simplified Molecular-Input Line-Entry System as the basic model, and further develops target guided generation by transfer learning. As results, ChemGenerator gains lower loss (<0.01) than existing reference model (0.2~0.4) and shows good performance in the case of Epidermal Growth Factor Receptor. Meanwhile, ChemGenerator is now freely accessible to the public by http://smiles.tcmobile.org. In proportion to endless molecular enumeration and time-consuming expensive experiments, this work demonstrates an efficient alternative way for the first virtual screening in drug discovery.

Global research on artemisinin and its derivatives: Perspectives from patents.

BACKGROUND: The isolation of artemisinin in 1971 heralded the beginning of a new era in antimalarial drug therapy, and artemisinin-based combination therapies are currently the mainstay of malaria treatment worldwide. Artemisinin-related studies have been extensively and intensively executed in the last few decades. However, although many purely technological reviews have been completed in this field, studies on artemisinin from the perspective of patents are still very limited. In terms of the importance of patents for academic research and commercial development, this study aims to reveal the overall patent landscape of artemisinin in the temporal, spatial, and technological dimensions. This work may provide a useful reference for relevant decision-making by researchers, investors, and policymakers. METHODS: All available patent data relevant to artemisinin derivatives and artemisinin-based drug combinations developed for use in various therapeutic areas were collected from the Derwent Innovation database. Descriptive statistics and citation analyses were used to analyze the patent landscape. RESULTS: A total of 4594 patent documents and 1450 simple patent families from 1986 to 2019 were analyzed. A comprehensive patent landscape of artemisinin is presented from the aspects of time trends, filing countries, patent ownership, co-patents, technological categories, therapeutic areas, and citation networks and pathways. CONCLUSIONS: China and the United States are mainly responsible for the dramatic increase of artemisinin patents over the last three decades. From the point of view of patents, notable technological issues on artemisinin are chemical and biological synthesis, novel combinations, new formulations and administration routes, drug repositioning, and minimizing the resistance. Furthermore, a critical challenge lies in how to stimulate the industry to develop artemisinin-related drugs by government regulation and public-private partnership.

Interactions of antithrombotic herbal medicines with Western cardiovascular drugs.

Thrombotic events act as a critical factor that interferes with Cardiovascular Diseases (CVDs), and antithrombotic herbal medicine is a long-standing controversial issue. Although a dispute is involved in their clinical application, all parties unanimously agree that herbal products have been widely used in folk medicine, and their interactions with conventional drugs are of high concern. This study aims to investigate how antithrombotic herbal medicines interact with Western cardiovascular drugs on the molecular level by taking an example of the most frequently used herbal pair, Danshen-Chuanxiong (DS-CX), and to discover more scientific evidence on their potential herb-drug interactions. Network pharmacology (NP), as an analytical approach of a complex system, is used to visualize and compare target profiles of DS-CX and Western cardiovascular drugs, which can be applied to predict common herb-drug targets and to construct a solid context for discussing herb-drug interactions. These interactions are further validated by in vitro assays, while in vivo zebrafish model employed for evaluating an overall pharmacological efficacy of herbal pairs in specific combination ratios. The study finds that DS could react directly to the Western cardiovascular drug targets relevant to antithrombotic pathways (i.e., thrombin, coagulation factor Xa and cyclooxygenase-1), whereas CX could not react directly and can synergistically affect antithrombotic effects with DS in specific combination ratios. Moreover, it is indicated that DS-CX may generate wide biological functions by a complicated mechanism of "neuro-immune-metabolism/endocrine" (NIM), which can further cause multiple direct and indirect interactions with Western cardiovascular drugs. From the clinical perspective, herb-drug interactions should be given high attention, especially when multiple herbs are used simultaneously.

Research and development of anti-Alzheimer's disease drugs: an update from the perspective of technology flows.

INTRODUCTION: Today, over 20 million people suffer from Alzheimer's disease (AD) worldwide. AD has become a critical issue to human health, especially in aging societies, and therefore it is a research hotspot in the global scientific community. The technology flow method differs from traditional reviews generating an informative overview of the research and development (R&D) landscape in a specific technological area. We need such an updated method to get a general overview of the R&D of anti-AD drugs in light of the dramatic developments in this area in recent years. AREAS COVERED: This study collects patent data from the Integrity database. A total of 399 patents with 821 internal citation pairs in the US from 1978 to 2017 were analyzed. Patent citation network analysis was used to visualize the technology relationship. EXPERT OPINION: For better production of anti-AD drugs, governments should emphasize the multi-target drug design, provide policy support for private companies, and encourage multilateral cooperation. The ß-amyloid peptide (Aß) theory leaves much to be desired; neurotransmitter and tau protein hypotheses are worth further examination. The use of old drugs for new indications is promising, as are traditional herbal medicines.