bluuebunny/crossref_metadata_2025 huggingface dataset:
Composition Analysis and Identification of Ancient Glass Products
Authors: Tan Quanwen
Published: March 2023

The glass manufacturing technology of ancient China is well known in the world. The study of ancient glass relics is of great significance for today's archaeology and glass aesthetics. In this paper, the logarithmic index of principal component analysis was used to reduce the dimensionality of glass, and then the decision tree method was used to classify glass into two categories, with a prediction accuracy of up to 93%. On this basis, the glass was subclassified, and the decision tree model was used to classify lead-barium glass and high-potassium glass according to whether they were weathered or not. Secondly, K-means algorithm was used to classify weathered glass according to weathering degree. Finally, the sensitivity of the model is tested from the two aspects of parameter selection and data disturbance. The re-judgment results show that the model has high accuracy and strong practicability.
The SCFAs Production of Syntrophic Culture of L. johnsonii SZ-YL and A. Muciniphila in Different Macrobutrients
Authors: Chen Yulin
Published: March 2023

The gut microbiota is a complex ecological system that influences numerous host physiology, such as obesity, appetite, immunity and drug metabolism. As a crucial component in intestine, short chain fatty acids (SCFAs) can modulate host metabolism and disease physiology via receptor, such as GPCRs. The system of knowledge of the host gut microbiota has been greatly expanded. Diets alterations can rapidly modify gut microbial composition and affect SCFAs production. Current knowledge of SCFAs production is mainly based on isolates or intestinal environment, but these may not reflect the effects of bacterial interaction on SCFAs generation. In these studies, the potential effects and SCFAs production of in a syntrophic coculture of L. johnsonii and A. muciniphila was investigated in different medium. Cocultures produced higher acetate and propionate in glucose and inulin medium. In oleic acid addition medium, the growth of L. johnsonii were promoted and the acetate production were promoted. These results indicate that appropriate diet proportion is necessary for beneficial bacteria growth to affect host health. Moreover, unsaturated fatty acid promotes the growth of Lactobacillus instead of A. muciniphila. Our results indicated that the changes of diet proportion might be potential method for beneficial bacteria growth.
Cancer Immunotherapy: A Brief History, The Latest Development of Typical Subtypes and Therapy Combination
Authors: Tan Shirong
Published: March 2023

The leading cause of death in humans has long been considered cancer. People have developed a variety of cancer treatments as science has advanced. However, the side effects and flaws of the therapies are still intolerable for patients. Cancer immunotherapy, which potentially can give a long-lasting treatment with minimal toxicities, finally appeared to address the inadequacies. Cancer immunotherapy keeps up with the advancements in contemporary health. In recent years, there have been many updates on the many subtypes of cancer immunotherapy. A brief history of cancer immunotherapy and the most current developments are summarized in this paper. The assessment also emphasizes the newest investment trend in cancer immunotherapy and prospective drug combinations.
The Correlation of the Mindfulness and Placebo Effect
Authors: Jin Lucy
Published: March 2023

The key finding in this paragraph was that, whether in a biological or functional sense, there are significant differences between the placebo effect and mindfulness therapy. Both methods trigger different brain regions to activate in function as intended, but there hasn't been reliable research to demonstrate this, and the multiple experiments that has been conducted has flaws. Therefore, further research is required to verify this occurrence.
Diabetes Mellitus with Membranous Nephropathy and H.pylori Infection: A Case Report
Authors: Zhang Siyuan
Published: March 2023

Early membranous nephropathy with diabetes mellitus is often easily misdiagnosed as diabetic nephropathy. Tacrolimus is a common drug for the treatment of membranous nephropathy, and CYP3A5 gene plays an important role in its metabolism. The decreased expression activity of CYP3A5 gene leads to the increased blood concentration of tacrolimus and adverse reactions. We report the case of diabetes mellitus with early membranous nephropathy and H.pylori infection in a 55-year-old female. Our patient was diagnosed with membranous nephropathy by renal puncture. Due to the slow metabolism of CYP3A5, tacrolimus was reduced to avoid side effects. After eradication of H.pylori, the patient’s urine protein decreased and the prognosis of membranous nephropathy was good. There was no discomfort during the follow-up period after the patient was discharged.
Strategies for Using CRISPR-Cas9 Orthologs to Perform Gene Editing Applications
Authors: Suo Zhikang
Published: March 2023

CRISPR-Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats -Cas9) is primarily the adaptive immune system developed by bacteria and archaea to defend themselves from an invasion of the virus. CRISPR-Cas9 is considered currently the most potential gene editing technology in 21 century due to its highest operationality and modifiability among the gene-editing tech that humans have ever found. Orthologous proteins are the proteins of different species which originally develop from one ancestor and still hold the same function as the original protein. This research mainly concludes and organizes the strategies for two specific types of Cas9 orthologs in the application of gene editing.
New Idea of Adopting Online Platform Sales for Rural Agricultural Products Backlog Problem Under Epidemic
Authors: Cui Hetong
Published: March 2023

Agricultural products are the basic national economy and an important pillar product to protect people's livelihood, "people are food for the day", food is the most basic human survival resource, the basic position of agriculture in the national economy, prominently expressed in the role of food. However, since the outbreak of the new corona virus in 2020, agricultural products around China have been stagnant,  and it is of great importance to actively respond to the call of the national policy for rural revitalization and high-quality agricultural development to help solve the problem of stagnant agricultural products. With the rapid development of China's Internet and e-commerce in recent years, it has become very common for China's traditional industries to involve in Internet platform sales, which has greatly broken through the restrictions of time and space and effectively reduced transaction costs. The rapid development of the agricultural products online sales industry is expected to gradually become a new development opportunity for agricultural products sales in the future. Therefore, this paper proposes a new idea of agricultural products-market-customer online sales based on the actual situation at present.
Spam Classification Based on Machine Learning Algorithm
Authors: Huang Yichun
Published: March 2023

As technology continues to advance, email is used in almost every field. However, the dramatic increase in the number of spam emails has led to a growing need for accurate and powerful spam classifiers. Unfortunately, spam in its many forms is constantly being updated as the Internet evolves, and the challenge of fighting spam is enormous. With the emerging of deep learning methods, deep based algorithms are widely applied in most of the real-world scene and tasks. In this paper, we used CNN, RNN, LSTM and naïve Bayes models to implement spam filtering, and compared them based on information such as accuracy, model strengths and weaknesses. We test all the models on the public dataset and measure them by four metrics, including accuracy, precision, recall and F1-score. Finally, we conclude that the naïve bayes model achieves the best performance among all those methods, which can deal with the threat of spam efficiently.
Efficient Spam Classification Using Machine Learning Methods
Authors: Miao Zhenghao
Published: March 2023

With the development of the times, we receive more and more information every day, and email is an important carrier of receiving information in our daily life. In this context, some spam came out, including some advertisements and false information. Therefore, it is necessary to classify spam and receive it selectively. Machine learning algorithms can classify and identify spam with high efficiency, and in this paper, we compare six models and achieve a top result of 98.7%. Spam classification can filter out unwanted emails at the receiving end, effectively saving people's time and preventing malicious users from stealing personal information.
Fashion Designer Application Based on Generative Adversarial Network
Authors: Liu Ziming
Published: March 2023

Embodying the design from scratches has been a common problem for all designers.  In some situation, clothes designers have trouble creating works that match their idea the most. Creating a fine work from a simple sketch is a tedious process of endless try-and-error. Designers spend days, weeks, or even months drawing drafts and discard them, because they need to draw the picture that best embodies the idea in their head. This study proposes a deep learning method that can generate clothes images from human sketch input, explores the effect of different image to sketch translators, different Generative Adversarial Network (GAN) architecture, loss functions and regularization methods. Many previous works have demonstrated strong results on conditioned image generation, and this study shows that similar settings can be transferred to help designers to embody their designs. The result shows that the model can generate clothes images with high fidelity while faithful to the input sketch.
Algorithm Comparison on Email Spam Filtering Task
Authors: Li Yixuan
Published: March 2023

Email has long been a major form of communication among organizations and individual users. In recent years, with the rise of internet use, email spamming has become increasingly common. Spamming has raised security concerns as it causes potential loss to the users with fake advertisements, invalid information, undetected virus, and other harmful information. Various techniques have been developed to facilitate spam filtering, using classifying algorithms to characterize emails into different categories. This article presents an investigation of how machine-learning-based algorithms are used in email spam filtering by providing some previous researches that have shown to be successful. The algorithms are in the range from supervised learning, including the Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Naïve Bayes (NB) to unsupervised learning such as artificial neural networks (ANN) and partitional clustering. This article also presents an experiment that compares different implementations of such algorithms, including the SVM, NB, and K-Nearest Neighbor (KNN). The results reflect that NB gave the highest accuracy. A second attempt of the same experiment was conducted, with an improved data cleaning procedure and larger testing sets. The data collected from the second attempt again show that the NB implementation gave the highest accuracy in detecting spam emails.
Fruit Classification based on ResNet and Attention Mechanism
Authors: Lin Miaorun
Published: March 2023

Numerous types of fruits are discovered, which can provide humans with nutrients and trace elements. There are 59 families and 694 species of fruits in China, of which more than 300 kinds of cultivated fruit trees are in abundance, including more than 10000 varieties. Therefore, the classification of fruit detection is very necessary. The traditional method of fruit classification mainly relies on manual methods, which has greatly reduced the cost effectiveness in recent years due to the increase of labor cost. This paper introduces the idea of transfer learning by comparing various automated methods for detecting and classifying fruits, and incorporates the attention mechanism module into the ResNet model to achieve recognition of image features that can effectively classify fruits. This paper seeks to provide a complete review on fruit classification concluding that the ResNet model with the introduction of the attention mechanism has good accuracy and verifying the efficiency of the model in the field of image recognition and classification.
Automatic Detection of Oranges Peel Based on the YOLOv5 Model
Authors: Ma Yukun
Published: March 2023

In recent years, the deep learning algorithms have been widely used in target detection with the development of artificial intelligence algorithms. This experiment tends to detect whether the oranges are totally peeled or not by using the YOLOv5 automatic detection system. By using this automatic detection, the factory can classify the peeled and unpeeled orange easily and successfully, hence improving the efficiency and quality of the production of orange products. To achieve this goal, this experiment uses the YOLOv5s.pt model for training the detection; for collecting the images, considering the real situation, this experiment collect the whole orange with peel, partly peeled, the whole orange without peel, and some cloves of peeled oranges; overall 1100 images were collected, 310 came from the real-life photos and other found online; the ratio of the number of training images and the validation images is 8:2; set up two classes which are “orange with peel” and “peeled orange”; Using the online tool to label the images for training; Using the PyTorch (1.12.1) as the deep learning library. The experimental result shows that the proposed method achieved 88.4% for the Mean Average Precision (mAP) value and 88.7% for the average recall rate. Besides, in the testing part, this result can successfully detect the “orange with peel” and the “peeled orange”.
The Development of Image Classification Algorithms Based on CNNs
Authors: Liu Qichang
Published: March 2023

Image classification is a method to process the given images by picking up the distinct features of different kinds of images to distinguish different targets in the image. The classification of images analyzes the given images quantitatively by using computers and divides the image or areas contained in the image into several categories instead of explaining them by human’s visualization. Image classification is an important research direction in computer vision technology and the basis for other applications such as image detection, behavior analysis, and object tracking. With the arrival of big data and the improvement of computer power, Deep Learning (DL) has swept the world, and the Convolutional Neural Network (CNN) image classification method has broken down the limitations of traditional image classification methods and has become a currently mainstream image classification algorithm. Thereinto, some typical architectures e.g., MobileNet, ResNet and VGG are attracted a lot of attention. This paper will review the development of the image classification and introduce some typical CNNs.
Composition analysis and identification of ancient glass products based on population forest-KNN algorithm
Authors: Chen Ziyuan
Published: March 2023

This paper is based on the KNN and Random Forest algorithms in machine learning to analyze the differences and correlations in the compositions of ancient glass objects, determine their classification and identify the unknown categories of artifacts. The classification rules of different types of glass are analyzed; for each category, appropriate sub-classification processes are performed according to their chemical composition, specific classification methods and processing results are given, and sensitivity and rationality analyses are performed on the results. The chemical composition of glass artifacts of unknown categories is analyzed, and then their categories are identified and sensitivity analysis is performed on their classification results. Samples of glass artifacts from different categories and analyze the relationships between their chemical compositions, and compare the differences that exist in the relationships between the chemical compositions of different categories.
Cybersecurity and Ethereum Security Vulnerabilities Analysis
Authors: Ma Tingyu
Published: March 2023

As computer technology develops, the popularity of cryptocurrencies and their use will grow, and the newer people enter the industry. It changes the business model between organized businesses out of the need for another trusted party. Blockchain smart contracts can automatically enforce agreed contract between two unknowns. Briefly introduce Ethereum, a cryptocurrency, and focus on the security of its smart contracts in internet transactions. Ethereum was the first platform to support high-level programming languages to implement smart contracts, and the second largest blockchain platform, providing a runtime environment for essentially all Decentralized Finance applications. Bitcoin also supports the development and execution of smart contracts, but it is affected by the nature of the programming language used, and it hardly supports transactions except for verifying signatures. Because smart contracts can support a variety of large transactions, some security vulnerabilities can be extremely costly. In an extensive search and survey, the issue of smart contracts for the Ethereum blockchain was valued. The article will discuss some of the existing or former contract vulnerabilities and their solutions. It concludes with a discussion of the future direction of the smart contract space and provides some suggestions for those researching the field.
Data visualisation analysis of online novel websites
Authors: Zhuo Meijuan
Published: March 2023

With the development of science and technology and the progress of the times, the online novel reading industry is also developing at a rapid pace, and online novel reading websites have also emerged. In order to make users better understand the current trend of popular novel genre popularity and give corresponding reference when users choose the novels to read. This study analyses novel creation data, novel creation genres, novel creation era, author writings and other data visualisation methods through bar charts, pie charts, radar charts, heat maps, word cloud charts and other data visualisation methods. Using web scraper, data on novel information is collected to ensure that the data is authentic and reliable. On the basis of cleaning the data using Python, the Echarts plugin is used to visualise the basic information of novels as well as the author's information to present the information of novels and readers in a more visual and vivid way. The study helps to obtain richer information about the novels and authors that one wishes to know, while making the readers' experience better and helping the website to operate and develop better.
Chinese Spam Classification based on Deep Learning
Authors: Chen Zhengyang
Published: March 2023

In the 21st century, it is an information age where individuals and organizations use computers to work and they commonly use email to chat with each other, share knowledge or their wishes or discuss business. However, in this context, spam is harassing our lives. Spam is a type of email that is delivered to lots of numbers of recipients without asking them for their wishes. Spam wastes our time reading useless messages and takes up our email addresses and network traffic. The problem of spam has become increasingly important and is growing over the years. The emergence of machine learning technology can simulate human intelligence. Use machine learning to identify the construct of pictures and words. Through this technology, this paper can classify the kind of different messages. Spam is very common nowadays; it can easily send lots of message to occupying a large amount of network bandwidth. Access such kind of messages, this article uses four models: Decision Tree, Support Vector Machine (SVM), Naive Bayes model, and Logistic Regression to identify spam to prevent it into our electronic mail.
Single Drug Therapy of PD-1/PD-L1 Checkpoint Inhibitors for Advanced Urothelial Bladder Cancer
Authors: Ge Hongze , Lee Hsuanyi , Liu Ye , Sun Ruijie
Published: March 2023

Since the first approval of Atezolizumab in May 2016, immunotherapy, PD-1/PD-L has completely changed the way bladder cancer is treated, as chemotherapy was the sole available choice as a treatment for bladder cancer, and the results still was not optimistic, with five licensed drugs treating bladder cancer. Despite the generally poor prognosis of advanced bladder cancer, some patients show persistent responses to immune checkpoint inhibitors. This review summarizes the efficacies and safety of the five drugs: Durvalumab, Atezolizumab, Avelumab and other drugs - from different studies respectively for treating advanced bladder cancer and mentions the side effects and future perspectives. For the treatment, all inhibitors that was licensed have akin efficacy and safety traits, but they differ in terms of dosage, frequency, and financial burden. Only Pembrolizumab, to date, has revealed advantage over conventional chemotherapy in a stochastic Phase III scenario. Pembrolizumab and Atezolizumab are also well tolerated and approved for patients who are unable to receive cisplatin treatment. Patients with bladder cancer now have some hope, thanks to immunotherapy. The current environment is continuously evolving, and new immunotherapy-combination trials are being conducted to further enhance results.
The treatments of Carvykti in Multiple myeloma
Authors: He Jintao
Published: March 2023

Multiple myeloma is a severe malignance caused by damaged B cells from bone marrow plasma cells. Multiple treatments have been introduced to release and treat such a disease, but in general, high rate and severity of adverse events and relatively unideal efficacies of those existing treatments necessitate a new therapy achieving a better curative effect. Thus, CARVYKTI, a CAR-T therapy, has been developed for treat patients with multiple myeloma and who have already received several other treatments. By having genetically modified T cells, damaged cancer-causing B cells are targeted and vanished specifically. Recently, the FDA has officially approved CARVYKTI as a treatment for refractory multiple myeloma, and the basic pharmacology and the phase1b-2 clinical trial are summarized in this paper.
Physiological Factors Affecting Diabetes in Women using Binary Logit Regression Model
Authors: Cao Yiming
Published: March 2023

The purpose is to use statistical methods to analysis some female data, trying to figure out what physiological factors will affect the occurrence of diabetes on female and how. Method: using dataset from “AKSHAY DATTATRAY KHARE” in Kaggle, which comes from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) in original. In particular, all patients here are females of Pima Indian descent who are at least 21 years old. Use binary logit regression model to analysis. Result: Pregnancies, skin thickness, insulin and blood pressure, as long as age can’t be taken into account (p>0.05). The remaining three elements, which is glucose (OR=1.039), BMI(OR=1.073), diabetes pedigree function (OR=3.130), are all risk factors. The overall correct rate is 78.3%. The conclusion is using binary logit regression model can analysis factors related diabetes well. The logistic regression model among the influencing factors of diabetes shows that glucose, BMI, and diabetes pedigree function are likely to cause diabetes, and diabetes pedigree function has a greater impact on the psychological function of patients.
Analysis of Exoskeleton Suit in Clinical and Home Use
Authors: Xu Jiacheng
Published: March 2023

The two most common causes of immobility that cause significant problems in everyday life are SCI and stroke. Recent research suggests that robotic exoskeletons may be able to help patients regain their motor function. This paper will evaluate existing exoskeleton suits, compare their functionality, and analyse their benefits and drawbacks compared to conventional rehabilitation equipment. It will also discuss the challenges it is encountering. It is discovered that the exoskeleton suit still requires more useable applications and precise design to meet clinical and domestic use.
Self-assembly of pH-responsive Prodrugs for Effective Antitumor Therapy
Authors: Zheng Jihan
Published: March 2023

A novel class of endosomal pH-responsive micellar nanoparticles was created by employing the self-assembly of an amphiphilic poly(ethylene glycol)-Schiff-doxorubicin (PEG-Schiff-DOX) drug. Under normal circumstances, these nanoparticles had excellent storage durability for at least 7 days, but they immediately disintegrated in a mildly acidic environment. Furthermore, a planned drug release behavior was seen, taking advantage of the different drug release mechanisms, which could lead to a higher intracellular drug concentration and longer action duration. The nanoparticles outperformed free DOX in anticancer efficacy against Hela cells, according to CCK-8 assays. Therefore, these prodrug-based nanomedicines hold significant promise for developing translational DOX tumor therapy formulations.
Reviews of drug candidates for COVID-19
Authors: Liu Meichen
Published: March 2023

The Outbreak of coronavirus disease 2019 (COVID-19) has become a global pandemic since December 2019. In order to combat the COVID-19, researchers have carried out many related experiments, including the pathogenesis of virus, to understand the structure and mechanism of the novel coronavirus. In addition, they have conducted in vitro and clinical trials for drug development. In this paper, the possible drug targets are discussed from the perspective of inhibiting virus entry into cells and inhibiting virus replication. In addition, the structure of the virus and its mechanism of entry into host cells are reviewed. Through this review, drug researchers can have a comprehensive understanding of the potential targets being investigated.
Traditional and Modern Rehabilitation Therapies of Ankle Sprains
Authors: Yu Chenying
Published: March 2023

The ankle joint is one of the main weight-bearing joints of the body. In the joint sprains, ankle sprains are the most familiar type. The ankle sprain is a damage to the ligaments surrounding the ankle joint and is commonly seen in athletes, paratroopers, sports enthusiasts and other groups. In the last few years, many researchers have executed studies on the treatment of ankle sprains, but there are still relatively few studies that summarize the discussion of ankle sprain treatment methods. This article presents the efficacy of traditional and modern rehabilitation therapy in ankle sprains by summarizing previous studies, aiming to promote the development of ankle sprain treatment research. Traditional rehabilitation treatment for ankle sprains includes tuina, acupuncture, fire pot and Chinese herbs-related treatment. Tuina therapy is conducive to peeling off adhesions, regenerating tendons and promoting the repair of damaged muscle tissues. Acupuncture can promote metabolism, accelerate absorption, and relieve the stimulation of various metabolic products on the sprained area. Modern rehabilitation therapies include physiotherapy, exercise, manual, and orthopedic therapy. Physiotherapy is the action of artificially generated or naturally available physical factors on the human body to prevent or treat diseases. Exercise therapy can promote joint fluid flow, facilitate local blood flow, and accelerate the absorption of inflammatory factors and the metabolism of cartilage.
Non-alcoholic Fatty Liver Disease: Pathology, Disease Models and Therapies
Authors: Wu Zhiyu
Published: March 2023

Non-alcoholic fatty liver disease (NAFLD) is characterized by a range of conditions induced through fat accumulation in the liver. This disease impacts population all around the world. NAFLD prevalence is rising at an alarming rate over the past years. To address the alarming increase in NAFLD prevalence, researchers are attempting to develop effective therapeutics to combat NAFLD. To develop NAFLD therapeutics, it is crucial to address current knowledge in NAFLD pathogenesis. Through summarizing current knowledge in NAFLD pathogenesis, researchers can better visualize current knowledge surrounding the disease and present knowledge gaps in the field. This review aims to deeply understand the role of three key NAFLD pathogenic factors: hepatic lipotoxicity, hepatic inflammation, and insulin resistance, and proposes potential target for NAFLD treatment. Furthermore, this review systematically summarizes current disease models and NAFLD therapies. In general, this review provides an overview of the progress of NAFLD and discusses reliable and practical models of NAFLD.
Gene Therapy for Alzheimer’s Disease
Authors: Liu Xiaoyang
Published: March 2023

According to CDC, Alzheimer’s Disease (AD) is the one of the most prevalent type of dementia from which the elderly tends to suffer. It is a progressive cognitive disease that have different stages with different severity. Usually, it begins with mild memory loss and loss function in language and response to the environment. Millions of people aged over 65 around the world are living with Alzheimer’s Disease. Until 2022, there are roughly 6.5 million Americans aged 65 or older suffering from AD. By estimation, in 2050, the population of AD is projected to reach around 12.7 million. Based on the fact that AD is a growing progressive illness from which aged groups suffer, it is urgent to look for possible treatments to AD. Currently, most available treatments are drugs that will palliate symptoms of AD, including improving cognitive functions and activities of daily living. However, traditional treatments take a long period to see progress, and patients can easily have drug resistance; they are not efficient enough. Fortunately, with the development in gene therapies, there are more possibilities in treating AD by targeting the pathological region in AD patients. This review systematically introduces treatments to AD, especially gene therapies.
Congenital insensitivity to pain: the controversy and possible pathophysiology model in progress
Authors: Xu Xiaohan
Published: March 2023

Congenital insensitivity to pain (CIP) is a disorder that emphasizes the critical role of nociception in protecting against tissue damage and is characterized by repeated injuries, burns, and poor wound healing. CIP is a developmental defect caused by pathogenic genetic variants in multiple genes. Current treatment modalities for patients with CIP are primarily symptomatic, but the first targeted therapies are being tested. Interestingly, this area of research offers new ideas for slow-moving pain, one of the great challenges still unresolved by the medical community.
Problems and prospects of PD-1/PD-L1 inhibitors
Authors: Shi Shenwei
Published: March 2023

The current gold standard for monotherapy or combination therapy for patients with advanced cancer is programmed death ligand 1 (PD-L1) and receptor 1 (PD-1) inhibitors, which are typical immune checkpoint inhibitors (ICI). Rarely do therapeutic responses of cancer treatment have the breadth, depth, and tenacity that drugs based on PD-1 do. The distinctions in effectiveness and toxicity of PD-1/PD-L1 inhibitors have drawn much interest since a number of solid tumors were authorized for treatment with PD-1/PD-L1 inhibitors. However, the drug resistance and prediction of PD-1 inhibitory therapy has troubled the patients when it comes to selecting the most suitable treatment scheme. Plus, the mAbs are not perfect drugs for some inevitable defects in physical and chemical properties. Exploring the structure of PD-1/PD-L1 inhibitors has to be done more. It goes without saying that focused attention should be given to the improved PD-1/PD-L1 inhibitors' structural design and enhancing ways of medication efficacy in order to improve PD-1-based immunotherapy for cancer treatment. For instance, the pharmaceutical industry anticipates that combining PD-1 inhibitors with other medicines to improve response rates would be a future research focus. Appropriate clinical biomarkers should be developed to refine the PD-1 inhibitor response population. As a result, here the basic structure and mechanisms of PD-1/PD-L1 inhibitors were concluded. The shortcomings and prospects of inhibiting PD-1 treatment are also covered.
Dopaminergic Neurons and Parkinson’s Disease: Current Status, Implications and Future Perspectives
Authors: Tong Fangze
Published: March 2023

Parkinson’s disease (PD) is a common neurodegenerative disease that impairs motor functions in the affected individuals, causing increased dependence and even mortality eventually. Therefore, it has become a significant resources and financial burden to the society. Scientists and companies have carried out a myriad of studies to study potentially effective drugs to slow or cure the disease, but they barely pass the Phase III stage of clinical trials. Under these circumstances, establishing the pathogenic mechanisms is really the key to removal of obstacles in the way of mitigating PD. Degeneration of dopaminergic neurons is known as a cause of motor manifestation in PD. Instead of approaching PD from the traditional α-synuclein theory, this review emphasizes on dopaminergic neurons per se to discuss their unique features and how they may implicate in PD development and progression. Some latest findings and potential future directions are also summarized and discussed in this review.
The Progression of Current Biomarkers for the Diagnosis of Alzheimer's Disease
Authors: Wang Shu
Published: March 2023

Alzheimer's disease (AD) is a common degenerative disease with no cure. Atrophy of brain tissue, accumulation of amyloid deposition, and neuronal tangles are its main features and the most commonly used biomarkers for diagnosing AD. According to them, cerebrospinal fluid (CSF) measurement and imaging techniques are currently the mainstream methods for AD diagnosis. However, the high price and the need for technology cannot meet people's willingness to screen on a large scale, so people are forced to look for new biomarkers in cheaper and readily available blood. This brief commentary divides into three sections (CSF, imaging and blood) to describe the biomarkers found in AD. Among these biomarkers, the current development direction (machine automation) and joint diagnosis research are briefly described for biomarkers incorporated into clinical standards. The present research status and limitations of biomarkers that have received significant attention are discussed. Finally, the article summarizes the current status of biomarkers in diagnosing AD and looks forward to the feasibility of biomarkers in blood in the future.
Ethical Challenges Posed by Brain-Computer Interface in a Medical Context
Authors: Xue Wentao
Published: March 2023

Brain-Computer Interface (BCI) is a group of relatively recent technologies that connects Central Nervous System (CNS) activity with an external device. The resulting interconnected pathway may possess a variety of functions, from extracting and showing electrical activity in the brain to modifying entire cognitive functions. Owing to its revolutionary capability of accessing individuals’ neural systems and modifying their mental states, BCI accounts for major breakthroughs in medical neuroscience, but are also ethically problematic. Under closer scrutiny, BCI notably gives rise to concerns relevant to privacy, autonomy, and identity, three basic rights of the individual. By focusing on ethical definitions, ethical scenarios, and two specific cases concerning vulnerable social groups, this essay examines the ethical repercussions of Brain-Computer Interface in the context of medical research and treatment.
Mental Health Problems Due To COVID-19 In Low-Income Group
Authors: Tam InPan
Published: March 2023

The changes in aggregate health indicators over eras of economic expansion and recession suggest that recent economic recessions trigger various mental health symptoms. A causal relationship between job loss and losses to one's psychological and physical health has also been demonstrated through studies. When there is a sharp macroeconomic fall, there are noticeable social class disparities in the frequency of mental health issues like depression, anxiety, and panic. The COVID-19 epidemic is shown from the viewpoint of mental health, and this article argues two of these causes; financial uncertainty and misery/depression/anxiety. The objective is to guide future psychiatric research on COVID-19 and mental well-being and to broaden the discussion of the differential impact. Scholars, mental health specialists, and community health workers are given recommendations on how to lessen the negative impact on it of vulnerable groups, especially those with lower incomes, those who need government assistance, and those with ongoing medical concerns. These persons might not have the appropriate social and financial resources to successfully deal with new social and psychological stressors. Anxiety, trauma, and Posttraumatic stress syndrome (PTSD) are among the mental health diseases that are most vulnerable in low-class society; these conditions are already the leading causes of disability globally, as per Global Burden of Disease research. Due to increasing exposure to established risk determinants, including economic burden, job uncertainty, and joblessness, the pandemic shows a spike in suicide rates globally.
The Current Status of Drugs Related to Amyloid β-protein in Alzheimer's Disease
Authors: Zhu Yanqing
Published: March 2023

Alzheimer's disease(AD) is the main cause of dementia, and the main patient group is the elderly, patients' cognitive ability will even degrade to difficult to live independently. According to the WHO 2020 statistics on dementia, there were about 50 million patients in that year. With the progress of the global aging, the number of AD patients will increase rapidly, which is becoming a global public health problem.Currently, the main drugs for AD are cholinesterase inhibitor, N-methyl-D-aspartic acid receptor inhibitor, and aducanumab which is open to the public and enters the Phase IV test in 2021. However, the current understanding of the mechanism of AD is still insufficient. In this article, we will introduce one of the current hypotheses for the pathogenesis of AD, Amyloid β-protein (Aβ) and aggregations, and describe a potential Aβ drug, Fc fusion protein, so that to provide more theoretical basis for the diagnosis and treatment of AD.
The Status and Development of Biomarkers of Alzheimer's disease
Authors: Huang Amelia
Published: March 2023

Alzheimer's disease (AD) is an extremely familiar form of the dementia. After the age of 65, the likelihood of developing Alzheimer's disease increases significantly. However, because the pathogenesis of AD is insufficiently clear, intervention and treatment at an early stage is particularly critical. Since 2011, biomarkers have officially become the standard for diagnosing Alzheimer's disease. Potential biomarkers carry out a significant role in clinical, studies and other areas. Although the cerebrospinal fluid (CSF), also the positron emission tomography (PET) are effectual in detecting neurodegenerative processes at an early clinical stage, they are widely unused in the clinic due to their high cost and invasiveness. Plasma biomarkers are expected to be a more convenient and inexpensive diagnostic modality. In this review, biomarkers based on individual pathological findings are summarized in three main categories: PET, CSF, and plasma. The paper outlines the development and application of biomarkers to date and mentions the challenges that still need to be addressed.
Non-pharmaceutical Treatment for Alzheimer’s Disease
Authors: Wang Xinyu
Published: March 2023

Alzheimer's disease (AD) has grown to be a serious issue for human health. It has overtaken cancer as the world's fifth leading cause of death. People have invested a lot of time, effort, and money in the process of Alzheimer's disease treatment, but there hasn't been much progress in pharmaceutical treatment for AD over the years. People can start with non-pharmaceutical therapies in addition to drugs. This paper discusses several effective non-pharmaceutical therapies for Alzheimer's disease. Sixteen articles were analyzed and used to analyze different treatments for Alzheimer's disease. The research examines nine non-pharmaceutical treatments, which included the removal of Aβ burden, stimulation of the hippocampus or entorhinal cortex, cognitive therapy, exercise, mental stimulation, reminiscence therapy, diet therapy, caregivers, and life care. A large amount of data is analyzed, and the results, benefits, and disadvantages of these treatments are compared. This research proves that non-pharmaceutical therapies are feasible ways to treat Alzheimer's disease and play a very important role in the treatment process.
Mechanism and efficacy of drugs for Alzheimer's disease
Authors: Ye Chencheng
Published: March 2023

Alzheimer's disease (AD) has become into a global concern to public health. Since it was first discovered in 1901, people have studied it for more than one hundred years, and many hypotheses have been proposed. However, its pathogenesis has not been completely revealed. In addition, the treatment and diagnosis of AD is a challenge worldwide, especially in low-income countries. Fortunately, however, some classical hypotheses have their validity, such as cholinergic injury hypothesis, Aβ cascade hypothesis and abnormal modification hypothesis of tau protein. And the drugs developed on the basis of these classical hypotheses have finally been proved to have therapeutic effects on Alzheimer's disease through continuous experiments by researchers. Among them, Aricept is a drug used in mild AD treating, which acts as cholinesterase inhibitor, while N-methyl-D-aspartic acid (NMDA) receptor antagonist Namenda is used to treat moderate or severe AD. This review reviews the background of Alzheimer's disease and its two available treatment medicines, called Aricept and Namenda, including drug mechanism, efficacy, safety and their pharmacokinetics.
Endoplasmic Reticulum Dysfunction and Parkinson's Disease
Authors: Li Yilin
Published: March 2023

An key organelle that manages protein quality and controls cell homeostasis is the endoplasmic reticulum (ER). When the misfolded proteins is builduped, its stress is brought on, and next comes the unfolded protein response (UPR). Long-term stress can cause cell apoptosis. Protein folding is particularly sensitive to neuronal cells, Now, many evidence-based researches can clarify the points: the stress of the ER stress and the UPR are closely associated with a large number of the illnesses that is neurodegenerative, including the Parkinson's disease (PD) and others. These illnesses are characterized by protein misfolding and accumulation. Numerous people are affected by PD. Parkinson's disease (PD) is caused by many factors, and the stress of the endoplasmic reticulum is actually one of them. The treatment of UPR pathway can alleviate the stress effect of ER to a certain extent, reduce the death of the nerve cells, and thus play a positive role in the treatment of this disease. This article will state the two exception mechanisms in PD and explore the potential therapeutic strategies targeting endoplasmic reticulum stress.
The Impact of Covid-19 Quarantine Policy on Mental Health among Adolescents
Authors: Lu Liangcheng
Published: March 2023

Since the COVID-19 pandemic, governments have implemented a variety of public health measures (social isolation, quarantine, lockdown, and curfews) to stop the spread of the coronavirus infection. These actions have significantly slowed the epidemic's spread, but they will also have some unfavorable impacts. According to reliable data, the experience of quarantine has a significant psychological impact on people of all ages, and its impact on mental health is very concerning, especially for adolescents. With reference to the body of existing literature, this paper seeks to investigate the effects of lockdown measures, such as isolation, in response to the COVID-19 epidemic on teenage mental health.
COVID-19 Diagnosis — A Current Review of Its Developing Trend
Authors: Huang Xinyue , Liu Mingyang , Zheng Yinghao
Published: March 2023

The COVID-19 pandemic has been confirmed as a public health emergency by the WHO in 2020. In order to deal with it, the first generation of diagnostic method such as the RT-PCR test has been developed. However, there is obvious shortcoming of these methods considering efficiency and patient’s feeling problems. Therefore, a series of SARS-COV-2 diagnostic technique has been developed based on the basic PCR test or migrating from the existing virus detection method. With reference to the issued literature, this paper aims at presenting the developing history of these SARS-COV-2 diagnostic methods and make analysis in extracting the logic behind it and make predictions about the future of these methods under the large-scale virus screening background nowadays.
Monoclonal Antibodies in Cancer Immunotherapy
Authors: Liu Xuqing , Xu Yunzhe , Zhang Muyang
Published: March 2023

The technology of monoclonal antibodies (MABs) was originated from the ideas that how antibodies of the B cells bind to the specific antigens to protect the body against foreign invasion. Nowadays, MABs drugs have been approved for more than 30 targets, they have been considered as one of the first-line immunotherapies which specifically target certain cancers. Due to their exquisite target selectivity and less toxicity, MABs have become the new mainstay of pharmaceutical industry. This review summarizes the history of discovery, basic structure, and in vivo production of the MABs. Meanwhile, this review introduces the basic therapeutic applications, mechanism and working process of MABs, MABs and its targeted cancers, issues with current MABs technology and corresponding methods of improvements are also discussed. Overall, MABs do have broad prospect in the future since its effectiveness of treating cancers with poor prognosis and wide therapeutic applications.
Targeting CD19 and CD22 with CAR-T cell therapy in acute lymphoid leukemia
Authors: Liu Zixu
Published: March 2023

Acute lymphoid leukemia (ALL) was usually occurred in children. It accounted for 75% of all acute leukemias. In other words, it accounted for 35 percent of all cancers in the same age group, especially Caucasian children. CAR-T cell therapy was an resultful treatment for ALL patients.CARs were artificial receptors. Their function was primarily to target lymphocytes, most commonly T cells, recognizing and eliminating cells that express specifically targeted antigens. There were some targets for CAR-T, such as CD19 and CD22. When treated with common methods, the prognosis of recurrent ALL after allotransplantation was frustrating. In specific the cell of CAR-T with CD19, B-ALL treatment was highly successful, 70 to 94% in a complete response (CR). therapy with CD19 and CD22 was targeted when treating refractory/relapse(R/R) B-ALL achieved high CR, most of patients couldn’t maintain enduring remission. This therapy was a huge success in curing leukemia, up to 60% of patients with this therapy relapse. To extend the period of recurrence-free survival, people targeted CD22 or CD19 antigen expression, respectively, treating relapse B-ALL patient after transplant treatment. The CR rate in single therapy with the first round achieved 85%. After that, among patients who completed CAR-T with CD19 and CD22, 88.5% and 67.5% were OS and EFS, respectively, between 12 and 18 months. The new strategy significantly improved treatment outcomes. In the future, the key of the research was shift to strategies with minimal cytotoxic chemotherapy and hematopoietic stem cell transplantation, and we hope can treat tumor successfully.