Despite sharing a border with China, the Lao People’s Democratic Republic (Lao PDR) announced its first COVID-19 case only on 24 March 2020, becoming the last country in Southeast Asia to report a confirmed case of the virus [Following the identification of nine cases by the end of March 2020 and the rapidly spreading outbreak in neighbouring Thailand, the Laotian government established a lockdown on 30 March 2020, banning international travel (except for key personnel) and mandating testing and quarantine of incoming visitors and migrant workers . AdditioRestrictions were relaxed within the next two months (from June to July 2020) and certain businesses, domestic travel, and schools began opening again. By June 2020, the government declared victory against COVID-19 following the discharge of all COVID-19 cases from hospitals, reporting no new cases for two months. Simultaneously, all individuals entering the country continued to be monitored with a 14-day mandatory quarantine, and in July 2020, over four thousand individuals were being monitored in isolation across the country . DespiteHowever, in 2021, Virachith et al.  investigAfter keeping the daily incidence below fifty for a long period (However, the emergence of new COVID-19 variants since January 2022 led to new waves of infections in the country. The situation especially deteriorated in March when the country registered 24 031 cases and 15 deaths in a few days, bringing the total number of deaths to 757 since the onset of the pandemic. In May 2022, however, the number of cases plummeted, and COVID-19 restrictions were consequently eased .These recurring outbreaks provide the public health community with an important lesson that no system is completely secure, and that contingency planning and emergency preparedness need to be implemented for any upcoming infectious disease outbreak or pandemic. Nevertheless, Lao authorities successfully stepped-up vaccination efforts, becoming the sixth country in Southeast Asia to reach the 70% landmark of vaccinating their population by mid-2022 . In one The successful implementation of COVID-19 vaccination plans was done after the Laotian government realised their shortcomings, manifested in the shortage of healthcare professionals, the unavailability of proper isolating facilities for infected patients, the inaccessibility of care and vaccination in remote areas, and the slow uptake of vaccines in the general population during the 2021 outbreaks . As the Despite being a low-income country and one of the poorest in Southeast Asia, Lao PDR has not only been able to prevent significant COVID-19 transmission, but also successfully dealt with the new waves of infections. The 2022 Lao PDR way of implementing public health responses may serve as a model for other resource-constrained LMICs.


The development of artificial intelligence (AI) allows for the construction of technologies capable of implementing functions that represent the human mind, senses, and problem-solving skills, leading to automation, rapid data analysis, and acceleration of tasks. These solutions has been initially implemented in medical fields relying on image analysis; however, technological development and interdisciplinary collaboration allows for the introduction of AI-based enhancements to further medical specialties. During the COVID-19 pandemic, novel technologies established on big data analysis experienced a rapid expansion. Yet, despite the possibilities of advancements with these AI technologies, there are number of shortcomings that need to be resolved to assert the highest and the safest level of performance, especially in the setting of the intensive care unit (ICU). Within the ICU, numerous factors and data affect clinical decision making and work management that could be managed by AI-based technologies. Early detection of a patient’s deterioration, identification of unknown prognostic parameters, or even improvement of work organization are a few of many areas where patients and medical personnel can benefit from solutions developed with AI. Artificial intelligence (AI) is considered to be the fundamental technology of the fourth industrial revolution, with global medical agencies signaling its value in constantly evolving medical care . By analNumerous institutions have recognized the value of AI not only as an additional tool for accelerated diagnostics, especially in the era of staff shortages, but also in providing patients with more comprehensive care. At the El Camino Hospital in Silicon Valley, predictive algorithms identified patients at a high risk of falling through the real-time comprehensive analysis of hospitalized patients’ data; the generated information about patients at risk was simultaneously transmitted wirelessly to medical staff, which resulted in a 39% fall-rate decrease within six months after the technology was introduced . The tecAs a result of a significant acceleration in technological development and the influx of more advanced applications, in 2019, the FDA Commissioner Scott Gottlieb outlined a novel review framework for medical devices implementing artificial intelligence technologies . In the The spread of the SARS-CoV-2 virus overcame barriers of countries and continents by utilizing the possibilities of globalization, forcing international organizations to search for new crisis-management solutions. Little was known about the new disease, and it was necessary to rapidly reduce viral transmission, identify risk factors, optimize management, and reduce the burden on hospitals that faced an influx of respiratory-compromised patients. The initial unknowns were quickly followed by emerging information chaos owing to a plethora of unverified data and their lack of systematization. It was mandatory to fill this niche promptly. International organizations turned for aid to novel technologies. The European Council intensively monitored AI-based technologies that were deployed globally . Most ofThe intensive work of multidisciplinary groups allowed for the development of the first AI-based technologies that could be implemented in hospitals facing the surge of COVID-19 patients. Support of the decision-making process has paramount importance when managing a large volume of patients, especially the interpretation of numerous radiological examinations to rule out non-COVID-19 causes of respiratory failure and to attempt to allocate patients who may develop a severe course of the disease. From the level of the hospital emergency department, AI-based tools for rapid COVID-19 diagnostics were created, among others, by Mount Sinai Health System (based on chest computed tomography (CT) scans and patient data) and the University of Minnesota, along with Epic Systems and M Health Fairview (chest X-rays) ,15. AnotBritish Medical Journal aiming at familiarizing medical professionals with the AI technologies [The World Health Organization (WHO) signaled that AI could be an important technology for overcoming the current global health crisis and a tool aiding sustainable recovery of populations, with an endorsed series of publications in the nologies . Howevernologies . Followinologies . It is mnologies . Utilizanologies . Formallnologies .Patients requiring ICU hospitalization have compromised chances of survival on their own and have to be supported with invasive treatment techniques related to decompensation of the cardiovascular and respiratory systems’ function. Hospitalization in the ICU also requires a significant individualization of patients’ treatment plans and focuses on a scholastic analysis of their whole clinical profile. Comprehensive intensive management significantly increases the time and resources that must be dedicated to patients’ care. Due to the course of the disease and the rapid emergence of large numbers of COVID-19 patients who required respiratory therapy, prone positioning, renal replacement therapy (RRT), or extracorporeal membrane oxygenation (ECMO), ICUs and their staff became swiftly overwhelmed. New ICU stations were created in rapidly adapted departments to provide the possibility of intensive care for as many patients as possible. After the initial resources crisis, when not enough personal protective equipment (PPE), ventilators, and ICU stations were available—a problem that could not be quickly resolved—there was a shortage of competent intensive healthcare professionals able to operate equipment and manage critical patients. In a short time, efforts were made to train non-intensive care personnel, an initiative that usually takes years under normal training conditions. A possible solution arose: to utilize clinically applicable AI-based technologies to support the decisions of healthcare professionals. The development of such technologies requires close interdisciplinary collaboration between AI developers and medical experts, especially because of the amount and implications of the information used by ICU healthcare professionals. Moreover, the role of AI in such a dynamic setting must be innovative in order to not disrupt the process of patient care and clinical decision making .Researchers started with development of tools that would help to predict the outcomes of the COVID-19 patients and adequately modify management to increase survival and allocate critical resources in the most optimal manner. A number of machine learning models were built to identify predictors of outcomes in the COVID-19 ICU . Based oAnother application of AI in COVID-19 intensive care is to predict the risk of more severe illness on initial presentation. Lazzarini et al. presented a machine learning model that could predict severe cases of COVID-19 such as acute respiratory distress syndrome (ARDS) and emphasized various risk factors that significantly impact disease progression . The stuThe AI-based technologies require a large volume of good-quality data to develop reliable algorithms, as the proposed solutions will only be as precise as the source information. The availability of healthcare data plays a crucial role in the implementation of realistic AI models in healthcare. The increasing digitization of healthcare systems and advancements in data storage and analysis allow for the generation and collection of numerous patient data such as electronic health records , medical imaging, genomic data, wearable device data, and more, providing valuable resources for training AI models. Robust datasets enable the development of more realistic and representative AI models that can better capture the complexities of real-world clinical scenarios. By incorporating data from different patient populations, geographical regions, and healthcare institutions, AI models can account for variations in disease prevalence, demographics, and treatment protocols that bring challenges in the real-world setting. In this way, AI models can identify previously unrecognized patterns, associations, or correlations within the data that may have significant clinical implications. These discoveries can lead to advancements in diagnosis, treatment, and healthcare delivery, ultimately improving patient outcomes, introducing more personalized medicine, and providing a platform for facilitating research and innovation, including drug discovery, disease modeling, and public health interventions. At the same time, the lack of explainability in AI algorithms may undermine trust and raise transparency concerns. Explanations for AI recommendations are crucial for bringing alignment with medical knowledge, as errors in AI systems can have severe consequences, making liability assignment challenging. Clear guidelines and regulations are needed to address legal and ethical implications and ensure accountability. The continuous learning of AI models poses challenges, requiring ongoing monitoring and validation for accuracy and reliability amid evolving healthcare practices. Unfortunately, despite the technological development, due to unconnected health record systems, barriers to the flow and collection of data are everywhere and occur between medical institutions, administrative regions, and countries. Full utilization of AI technologies’ potential will require integrated data analysis systems. The AI algorithms are based on data and rules obtained from specific disease entities, comorbidities, and ethnic and population data and based on the currently available medical knowledge. In order to create universal tools, it will be necessary to include geographically, socioeconomically, and gender-diversified groups. The undertaking of development works will have to take into account an even greater identification of variables that might influence the prognosis but that would not, however, impact the generalization of the algorithms. Even though those criteria would be met, it is mandatory to acknowledge that AI technologies can facilitate the work of medical personnel, but the decision-making process cannot be solely dependent on them. In the case of the emergence of a novel management or a new disease characterized by a different course, the previously created AI system may return incorrect information based on the analysis of heterogeneous data in the context of previously imputed information. AI models should demonstrate robust performance across diverse patient populations, clinical settings, and data sources, allowing for the generalizability of AI systems among various demographics. Additionally, validation of AI models is mandatory to identify and address potential biases and ethical concerns, ensuring the models do not disproportionately favor or disadvantage specific populations and promoting fairness and equity in healthcare delivery.Typically, the predictions of the currently developed AI models are more optimistic than their clinical performance. This was the case with the EPIC sepsis-alleviation system, which was implemented in numerous hospitals in the United States and performed worse than initial predictions suggested—after an analysis of nearly 40,000 hospitalizations, it only correctly identified 63% patients at their risk of sepsis compared to 76–83% identified by the designer’s predication curve .Another impact of AI on the medical field is ChatGPT. The generative pre-trained transformer (GPT) is a class of language-learning models (LLM) introduced by OpenAI  in 2018. ChatGPT has successfully completed the three United States Medical Licensing Exam (USMLE) tests . AdditioCascella et al. asked ChatGPT to create a medical report for a patient in the intensive care unit with details about ongoing therapies, laboratory samples, blood gas analysis parameters, and respiratory and hemodynamic factors in a random sequence . Upon reWithin the healthcare sector, GPT may take on roles in research, education, and clinical care . In reseThe AI-based technologies have a number of pitfalls, including reliability, responsibility, privacy, transparency, and security. After the G7 Health Ministers’ Meeting in Oxford on 4 June 2021, announcements were issued on regulations of AI systems’ management . Due to During the pandemic, managing law and ethics faced an unprecedented global challenge. Informatization allowed for a previously unparalleled scope of access to personal data, which can be implemented to assemble large and detailed databases for AI-enabled programs. This phenomenon initiated a discussion on data privacy and personal health data ownership since some organizations exchanged patients’ data with technology businesses and startups in order to assert the development of novel and potentially life-saving AI solutions. Concurrently, those issues can jeopardize dataset representativeness and result in the omission of certain populations. While data exclusion due to the selection bias originating from the lack of consent and data anonymization of patient demographics protect individual privacy, they can result in potential bias and inaccuracies of AI-based prognosis, which can in turn affect specific populations. At the same time, it is necessary to create legal norms and regulations that will govern AI technologies, their developers, and users, as one of the problems with implementing AI-based technologies is liability for errors and damages related to its use.Developing techniques, creating interdisciplinary teams, training medical staff in the scope of available solutions, adapting IT networks, as well as creating legal regulations should now go hand in hand in order to optimally ensure the development of AI medical personnel support.It is necessary to create interdisciplinary teams that will include clinicians, people who know AI modeling, IT specialists, lawyers, and people responsible for the ethical development of the above technology. We can gain a great deal as we slowly pursue the possibilities, but the appropriate units must uphold the rule of law, legal responsibility for the use of AI, and more than ever, ensure data safety and the full respect of data confidentiality and patient rights.Artificial intelligence has yet to reach its full potential; now is the time to consider the limitations and gaps and learn the lessons needed to create the sustainable, resilient, and citizen-centered future of AI.


Tick-borne viral diseases (TBVDs) of domestic livestock pose severe threats to global food security, economies of nations and public health due to their negative consequences on farmers' incomes as well as human and animal health , 2. AdeqBratuleanu et al. reported the detection of novel viral sequences in Rhipicephalus sanguineus ticks collected from small ruminants. These novel viruses belonged to the Phenuiviridae (Brown dog tick phlebovirus 1 and Brown dog tick phlebovirus 2) and Chuviridae  families. Surprisingly, sequences from a novel quaranjavirus-like virus, tentatively called Cataloi tick virus, were also identified in these hard ticks. The authors concluded that the discovery and characterization of tick-transmitted viruses would have consequences for virus taxonomy and provide better understanding of tick-borne viral zoonoses.The increasing incidence and geographical distribution of tick-borne viruses underscore the animal and public health importance of these arboviruses, especially with the rapidly changing global climatic conditions. In a study conducted in Romania, one of the most biogeographically diverse countries in Europe with conducive environment for the establishment of tick-borne virus foci , BratuleQin et al.). However, the emergence of some unknown TBVDs pathogens and the lack of data on tick virome underscores a crucial need for active viral surveillance and discovery in ticks, thereby promoting knowledge on the biodiversity and evolution of tick-transmitted viruses . To gain better understanding of the spectrum of viruses borne by ticks and detect the likely viral pathogens, profiling of viruses in ticks is necessary. Using metagenomics sequencing, Qin et al. characterized the virome in three major tick species  associated with pathogens in North China. They identified 28 RNA viruses belonging to more than 12 viral families of which Dermacentor pestivirus-like virus, Chimay-like rhabdovirus, taiga tick nigecruvirus, and Mukawa virus were recognized as novel viruses. Additionally, they detected Nuomin virus, Scapularis ixovirus, Sara tick-borne phlebovirus, Tacheng uukuvirus, and Beiji orthonairovirus which are already recognized as human pathogens with unknown geographical distribution and pathogenicity.The re-emergence and unceasing spread of recognized TBVDs such as Crimean-Congo hemorrhagic fever virus (CCHFV) positively correlate with the rising cases of TBVDs in humans and animals , studied the epidemiology of CCHF at the tick-domestic livestock-ecosystem interface in France and identified different factors that could explain the prevailing situation.Crimean-Congo hemorrhagic fever virus is maintained in nature he virus . This vihe virus . Despitey fluids . The disy fluids , 10. In  animals , 12, sugPerveen and Khan examined the epidemiology of CCHF in the Arab world from 1978 to 2021. Although the review documented widespread infection of several animal species as evidenced by serological assays, CCHF was most frequently only recognized following fatal human infections. Like Europe, Hyalomma ticks appeared to be the most common vector of CCHF in the Arab world; however, the role of Rhipicephalus species has not been extensively investigated. Most importantly, a consensus of all the 57 studies examined is that CCHF is an occupational hazard among workers in the livestock processing industry. The review highlighted the need for a more focused surveillance activity to describe the epidemiology of CCHF in the Arab world. This call is apt at a time when many tick vectors are rapidly expanding their geographic ranges due to changes in global climatic conditions. Otherwise, an endemic viral infection in the Arab world could soon become an epidemic in Europe and the rest of the world.Contrary to its current epidemiology in Europe, CCHF is an endemic disease in the Arab world, a term that describes a large geographically heterogeneous area that covers the northern part of Africa and extends to the Levant. In their systematic review, The results of these studies and reviews not only provide new relevant information on the extensive diversity of RNA viruses in ticks, but they also offer a basis for further studies on the interactions among domestic livestock, ticks and tick-borne viruses. Besides, they provide better awareness of tick-borne viruses and the possible threat they constitute to ruminants and humans. They are also valuable for preventing possible outbreaks of TBVDs of livestock through vector control. Additional studies to elucidate the geographical distribution, infectivity, and pathogenicity of these tick-borne viruses are required.DO wrote the introduction and conclusion, while all authors contributed to the central sections with comments to the cited papers and references. All authors read and approved the submitted version.


During the COVID-19 pandemic, restrictive measures were imposed that significantly impacted the healthcare system in general, and the dental healthcare system in particular. The literature cites a possible association between mental and oral health, as psychiatric patients have decreased awareness of their oral health and, therefore, poor dental status. Moreover, several studies have found a positive association between SARS-CoV-2 infection and oral health conditions, as well as between SARS-CoV-2 infection and mental health status. This context generated multiple ethical dilemmas in the case of persons with mental health disorders who require dental treatment because they are more vulnerable in this respect. This article aims to analyze the ethical issues in dental care for patients with mental disorders concerning the COVID-19 restrictive measures. The ethical aspects involved here are the basic principles of bioethics and the related elements of accessibility, equity, consent, and confidentiality. During the COVID-19 pandemic, restrictive social healthcare-related measures were imposed, which were required to properly manage a large number of infected patients, but also to protect citizens from disease transmission. The main route of transmission of the virus has been found to be airborne via small infected fluid particles (including aerosols) from the sick person when coughing, talking, sneezing, or breathing . Thus, gIn this context, at the level of the general population, amid uncertainty and restrictive measures, common psychological reactions such as stress, anxiety, depression, frustration, panic, hopelessness, and despair, including self-harming behavior, were observed ,5. The iIn the same manner, studies have found a positive association between SARS-CoV-2 infection and oral health conditions such as xerostomia, aphthous lesions , orofaciConsidering the above-stated facts, a complex interconnection between COVID-19, mental health, and oral health exists, which is summarized in The main ethical issues in the dental care of patients with neurocognitive disorders before the COVID-19 pandemic, identified according to the literature on this topic, for example purposes, are listed in The purpose of our article is to analyze the ethical implications of the COVID-19 pandemic on oral healthcare in patients with mental illness.We analyzed the scientific literature on moral principles and values related to oral healthcare for psychiatric patients during the COVID-19 pandemic. The search was conducted on Web of Science, Scopus, PubMed, and Google Scholar for peer-reviewed research that explores the dental approach to patients with psychiatric symptoms or disorders during the COVID-19 pandemic from a clinical and ethical perspective. The included literature focused on oral health structures in relation to the aforementioned populations with special needs, through the impact of the restrictive measures implemented during the pandemic, with their repercussions on the medical act and the patient. We also took into account scenarios centered on particular patient cases exposed to the general public, as well as the reactions and medical methods of adaptation generated.As a general rule, during the early stages of the COVID-19 pandemic, dental beneficence has been deprioritized in relation to nonmaleficence, as the health-related risks associated with disease transmission, both for patients and physicians, have been considered higher than the consequences of postponing dental care . Dental Veracity is one of the pillars of the physician–patient relationship, involving therapeutic premises and patient expectations. Truthfulness confers respect for the autonomy of the patient or the parental/legal guardian authority in the decision-making process, with the patient’s best medical interests as its objective. To achieve the goal of veracity, physicians have a duty to prevent the promotion of misinformation, and therefore, speculative and misleading therapies. In the initial pandemic phase, external anxiety and caution prevailed in the absence of sufficient definitive evidence regarding COVID-19 to underpin medical practice in this regard . In psycFurthermore, the COVID-19 pandemic has created uncertainty surrounding the accuracy of medical information as well as the effectiveness of certain treatments and investments in nonstandardized bio-decontamination equipment . StudiesIt is crucial for dental professionals to prioritize providing accurate medical information to patients . HoweverTriage and informing patients of the risks of viral infection is mandatory, and confidentiality can be breached regarding the patient’s COVID-19 status with the maintenance of standards of care . In partThe oral health of mental health patients and persons with special needs is frequently overlooked due to their lack of motivation and/or lack of awareness, dental treatment phobias, and poor economic situation. Common barriers such as decreased awareness, decreased expression of physical discomfort, and dependence on family members to reach the dental office or to provide treatment expenses are well known . PatholoIn the same sense, the absence of professional training for dentists regarding patient care for patients with special needs, the risk of stigmatizing this vulnerable population group, and the lack of training for psychiatrists on oral health screening , combinePhronesis is based on practical experience and determines a person’s ability to perceive a situation to deliberate and act appropriately in given circumstances . The panFor people with mental disorders, stigma can be extrinsic (public) but also intrinsic (self-stigma) . In addiThe pandemic has caused a decrease in the number of dental procedures, leading to financial struggles in the dental profession. This is concerning, and there is a need for the profession to recover by prioritizing preventative services and ensuring equal access to oral health services .In the COVID-19 pandemic, telemedicine, which was already perceived as a promising tool for the prevention and promotion of oral health ,71, gainAlthough seemingly salutary given the particularity of the situation, teledentistry involves certain ethical challenges, including confidentiality, which may be compromised by breaches in information security  and infoThe duty to treat infected patients is based on four considerations: duty as an intrinsic moral obligation, duty as a response to a given trust, duty as a professional norm, and duty as an employer-imposed norm .The provision of dental care involved medical risks for dentists in the initial pandemic phase with limited protective materials. Additionally, through the lens of neurocognitive disorders, a patient may be noncompliant or exhibit negative behaviors, which gives the clinician the right to refuse to initiate the therapeutic alliance as long as the patient’s dental status does not represent a dental emergency. Treatment refusal may be due to multiple causes, including cultural differences, inadequate (poor/excessive) information, information from different, contradictory sources , physicians’ verbal and nonverbal communication, and medical conditions that may alter the decision-making process and implicitly lead to refusal of treatment . AccordiIn the COVID-19 scenario, the refusal or interruption of the physician–patient relationship was questionable, with the physician having the obligation to treat in the situation of dental emergencies. In support of this obligation came the further obligation of the physician to have and use protective materials  as well the patient’s obligation to provide the necessary information during the triage procedure about COVID-19 status, personal contacts, and symptoms. The drastic measures took into account the possible unfavorable consequences generated by the potential contamination of the physician, which would have required the interruption of his activity and the accentuation of the staff shortage, as well as the scenario of the physician becoming a vector of transmission of the SARS-CoV-2 virus both professionally (patients and colleagues) as well as on a social level , which, Although a higher prevalence of dental diseases among people with mental disorders is known, the issue of dental treatment is rarely addressed in the literature, which can be considered a limitation of this review. Suggestions to improve oral health in people with special needs include prophylactic dental programs in the context of interdisciplinary psychiatrist–dentist collaboration, the implementation of appropriate preventive dental measures, and easily accessible regular check-ups . The impThe global impact of COVID-19 has rendered individuals with mental disorders more susceptible, and consequently, their dental healthcare has been adversely affected. It is crucial to acknowledge this reality and implement measures to prevent future circumstances that could inflict irreversible harm upon patients and the healthcare system. Safe and regulated means of obtaining dental services must be prioritized, while also analyzing the ethical implications of medical practices and their effects on vulnerable groups.


With the degradation after aging and the destruction of high-intensity exercise, the frequency of tendon injury is also increasing, which will lead to serious pain and disability. Due to the structural specificity of the tendon tissue, the traditional treatment of tendon injury repair has certain limitations. Biodegradable polymer electrospinning technology with good biocompatibility and degradability can effectively repair tendons, and its mechanical properties can be achieved by adjusting the fiber diameter and fiber spacing. Here, this review first briefly introduces the structure and function of the tendon and the repair process after injury. Then, different kinds of biodegradable natural polymers for tendon repair are summarized. Then, the advantages and disadvantages of three-dimensional (3D) electrospun products in tendon repair and regeneration are summarized, as well as the optimization of electrospun fiber scaffolds with different bioactive materials and the latest application in tendon regeneration engineering. Bioactive molecules can optimize the structure of these products and improve their repair performance. Importantly, we discuss the application of the 3D electrospinning scaffold’s superior structure in different stages of tendon repair. Meanwhile, the combination of other advanced technologies has greater potential in tendon repair. Finally, the relevant patents of biodegradable electrospun scaffolds for repairing damaged tendons, as well as their clinical applications, problems in current development, and future directions are summarized. In general, the use of biodegradable electrospun fibers for tendon repair is a promising and exciting research field, but further research is needed to fully understand its potential and optimize its application in tissue engineering. Under continuous economic pressure and a global aging environment, the treatment of musculoskeletal diseases is still a major challenge. As a component of the musculoskeletal system, the tendon is the connective tissue connecting muscle and bone, which can store and transfer energy during exercise and play a buffer role. As the tendon bears repeated load strength, it will lead to tearing and pathological changes of the tendon, and then cause pain, swelling, loss of tissue integrity, and functional damage ,2. At prWith the maturity of electrospinning technology and the development of technology, electrospinning has a variety of spinnable materials, simple devices, low preparation cost, controllable process, and high production efficiency. The nanofibers prepared using this technology have the advantages of a large specific surface area, high porosity, and adjustable diameter, which can mimic the natural extracellular matrix (ECM) in morphology, so it has great potential in tendon repair ,6. ElectDifferent preparation methods and raw materials have an impact on the morphology and properties of the final fiber. By selecting the appropriate polymers and process parameters, it is easy to produce fiber structures with different morphologies from tens of nanometers to several microns in diameter, and at the same time, it can produce ECM nanofiber scaffolds with high mechanical strength and bionics . In addiThe purpose of this review was to summarize the different structures of tendon repair product scaffolds prepared using electrospinning technology and their applications in the biomedical field . BiodegrNatural tendon tissue has a layered fiber structure, which is composed of collagen arranged into fibers (type I collagen accounts for 95%) and cells with highly anisotropic mechanical properties. Tendon cells belong to the fibroblast family and are the most common cell type in tendon tissue. They are responsible for forming the structural framework of tendons and can effectively transmit force during muscle contraction . CompareThe first stage of tendon healing is the short cell phase of tendon cells and inflammatory cells invading the wound. After the injury, the initial inflammatory phase begins after a large number of cells die. Subsequently, inflammatory cells, such as neutrophils, monocytes, and macrophages, infiltrate the damaged area. The second stage is the proliferation stage of fibroblasts, which involves the migration of cells to the injured site and the proliferation and deposition of collagen fibers. Finally, in the remodeling stage, which lasts from several months to several years, tendon cells and collagen fibers are arranged along the longitudinal axis of the tendon in the direction of stress, the production of type I collagen increases, and the number of cells decreases . Tendon Common biodegradable polymers used in tendon tissue engineering include natural biodegradable polymers and synthetic biodegradable polymers. Compared with synthetic polymers, tendon tissue engineering scaffolds prepared from natural polymers have unique advantages: better cell activity and adhesion, as well as a higher biocompatibility and degradation rate than other materials . Common In tendon tissue engineering, collagen, as the main component of the human tendon, is a natural degradable polymer with a biomimetic tendon ECM structure. Due to its good cell and growth factor binding sites on the surface, it has the function of supporting cell adhesion, migration, growth, and differentiation . Tissue Silk proteins have good strength and toughness compared to most natural biodegradable polymers  and haveGelatin is a unique fibrin, a collagen derivative that mimics the natural connective tissue microenvironment . It signAlthough biodegradable polymers have made great strides in the field of regenerative medicine, it is still difficult for any single polymer to meet all the necessary biochemical needs . In ordeElectrospinning technology occurs when a viscoelastic polymer fluid is extruded from a spinneret under the electrostatic repulsive force of a strong electric field, and the surface tension produces a hanging droplet. After electrification, the electrostatic repulsion between surface charges with the same symbol causes the droplet to be deformed into a Taylor cone, and the charged jet is ejected from the Taylor cone . DiffereTendon is a highly anisotropic tissue, in which the collagen fibers are arranged uniaxially and parallel to each other. Tendon fibroblasts showed highly organized and randomly oriented morphologies in aligned and random parts, respectively . UniaxiaInspired by the multiscale helical fiber structure of natural biological tissue, the helical nanoyarn with a multiscale structure can be prepared using electrospinning and continuous twisting technology. The structure has excellent mechanical properties and ultra-high extensibility. The multiscale periodic topological structure on the material surface can not only change the physical characteristics of cells , but can also induce the directional differentiation of mesenchymal stem cells into muscle cells by regulating the transport of cell types and specific transcription factors to the nucleus . ElectroWhen tendons are injured, it is difficult to balance the relationship between exercise and rest. Fortunately, Wang et al. achieved the goal of repairing tissues while exercising properly. They first prepared a kind of electrospun nanofiber composite membrane with a PCL/polyurethane (PU)/PCL sandwich structure, then twisted the fiber membrane into a straight yarn, and then further twisted it to form a spiral yarn support. Due to the non-planar movement and high extensibility of the scaffold, when the rat bone marrow cells cover the whole scaffold to stretch the scaffold, the cells can maintain a high survival rate under the cyclic strain, and gradually proliferate with the passage of time B 19]. I. I19]. I®, DP) are biocompatible and biodegradable, and have proven to be ideal tendon materials for electrostatic spinning tubes [In the surgical treatment of a ruptured tendon, the development of a nanofibrous tube that prevents penetration between the tendon and the surrounding tissues is a possible solution to improve the adhesions that may occur at the injury site in order to cope with the bleeding and infection during the healing process that lead to adhesions. Copolymers of polyhydroxybutyrate and ε-caprolactone  used in the clinic, SLNMs can significantly reduce the adhesion around the tendon  to further enhance their physical and chemical properties and biological activities A. The stDue to the uncontrollable parameters during the preparation of traditional electrospinning technology, the prepared electrospinning products usually have small pore sizes and random fiber diameters, which is not enough for cell infiltration and growth . TherefoThe shape and diameter of products prepared using electrospinning technology mostly depend on the process parameters. With the update in technology, the fiber diameter, diameter distribution, and orientation of electrospinning products are within the controllable and adjustable range as a result of controlling the conductivity, electric field strength, solution concentration, auxiliary electric field, and other factors ,86,87,88However, the weak mechanical properties of electrospun materials are a problem that cannot be ignored, and they are usually not suitable for hard tissue regeneration. It is a feasible method to enhance the tensile strength and other mechanical properties of electrospun products through subsequent extrusion, heating, and other methods . At the The use of exogenous growth factors has the potential to accelerate cell proliferation, collagen synthesis, and extracellular matrix synthesis, thereby accelerating recovery and enhancing repair. The basic fibroblast growth factor (bFGF) is usually selected as a representative growth factor that affects and enhances tendon/ligament repair and healing, cell differentiation, diffusion, proliferation, and ECM production . ConsideDue to the limited number of stem cells in tendons, the low activity/repair ability severely limits the ability of tendon regeneration. MSCs have a strong self-renewal ability, differentiate into various cell lines, and produce abundant functional paracrine factors. Therefore, MSCs-mediated cell therapy has great potential as a new strategy for tendon tissue regeneration. An SF/methacrylic acid hydrogel (GelMA) bioactive nanofiber scaffold D designeAdipose-derived stem cells (ADSCs) are easy to obtain, have a large storage capacity, and have the potential to differentiate tendon cells. The mesh scaffold composed of a longitudinally arranged PGA fiber inner layer and a braided PGA and PLA fiber outer layer is evenly inoculated with ADSC on the fiber scaffold, and then implanted into the injured Achilles tendon after expansion in vitro. For the treatment in the rabbit Achilles tendon injury model, with the increase of implantation time, the cell seed constructs gradually formed new tendons and became more mature at 45 weeks. A histological examination confirmed the similarity between the new tendon and the natural tissue. Compared with the normal tendon, the tensile strength of the treatment group reached 60% . Skeletal muscle-derived cells (MDCs) are a mixed cell group containing muscle cells, fibroblasts, satellite cells, and muscle-derived mesenchymal stem cells. Compared with mature and fully differentiated tendon cells, MDCs have higher proliferation potential . MDCs frThe performance and function of the original polymer structure can be enhanced by adding nanoparticles into the electrospun fiber. Rinoldi et al. incorporated silica nanoparticles into the beaded electrospun fiber structure, which could improve its wettability, stiffness, and degradation rate, and was conducive to cell proliferation and extracellular matrix deposition . HydroxyInfection after tendon surgery seriously prolongs the repair cycle. Due to the significant antibacterial activity of silver nanoparticles (Ag NPs), many studies have added them to the nanofiber scaffold to effectively reduce the inflammatory reaction and, thus, reduce the adhesion of tissues around the tendon ,100,101.In order to improve the biological reaction of electrospun nanofiber structure, the use of hydrogels with excellent performance is also a feasible strategy. Rinoldi et al. coated a thin layer of GelMA hydrogel containing mesenchymal stem cells on the electrospun nanofiber substrate of PCL/nylon-6 to prepare an optimized 3D multilayer composite scaffold, which can achieve sufficient mechanical and physical properties as well as cell viability and proliferation. Bone morphogenetic protein 12 (BMP-12) was added to promote the differentiation of MSCs, and mechanical stimulation was performed on the scaffold containing cells to imitate the natural function of tendons. The results showed that the synergistic effect of mechanical and biochemical stimulation was conducive to the enhancement of cell viability, proliferation, arrangement and tendon differentiation .The sliding compression of the tendon is prone to rupture of the hydrogel, leading to changes in the polarity of macrophages related to biomaterials and inducing inflammation . The hydThe combination of electrospinning and other advanced technologies makes up for their respective technical defects and can give full play to the advantages of multitechnology cooperation. For example, electrospinning combined with 3D printing technology shows controlled mechanical properties and improves cell adhesion and proliferation . Touré eMultitechnology cooperation can improve performance in many aspects. Melt deposition modeling, melt electrospinning, and solution electrospinning can provide structural support, promote cell arrangement, and create bionic microenvironment to promote cell functioning. The surface modification of plasma can improve the hydrophilicity of the scaffold and creates a bionic microenvironment to enhance the ability of cell adhesion and proliferation . FurtherThe 3D structure of electrospun fiber is similar to the natural ECM structure of a tendon, which can provide scaffold for tissue growth and support the organization and arrangement of cells in tissue. Meanwhile, it supports the infiltration of cells and nutrients, and promotes the proliferation and regeneration of tendon tissue. Through specific design, the electrospun 3D scaffold has its advantages in the three stages of inflammation, fibroblast proliferation, and remodeling A.Inflammation coexists with the early degeneration of tendon, and the interference between immune cells and tendon fibroblasts will lead to poor tissue healing. The disordered fiber surface may affect the adhesion and gene expression of tendon cells, and make them produce pro-inflammatory signals . In respThere is an inseparable relationship between the formation of adhesion and the expression of inflammation. It is an effective way to use anti-inflammatory materials to reduce the inflammatory reaction around the tendon. The nanofiber membrane with a polyethylene glycol/polycaprolactone/Ag NPs shell and hyaluronic acid/ibuprofen core prepared with coaxial electrospinning can reduce the adhesion of fibroblasts, and the core–shell structure can reduce pain and increase antibacterial activity by releasing ibuprofen and silver nanoparticles. At the same time, the combined effect of AgNPs and ibuprofen leads to the reduction of macrophages on the tendon tissue to reduce infection and inflammation, so as to meet the needs of an ideal antiadhesion barrier .3D-oriented electrospun fibers exhibit flexible controllability in morphology and fiber density, have excellent biocompatibility in vitro, and are conducive to promoting cell adhesion, proliferation, and differentiation on its microstructure ,116. In +/CD68+ scar subpopulation membrane identified in the immune landscape after tendon injury to balance tissue damage. Him-MFM implanted into tendon can change the polarization of type I macrophages, reduce cell apoptosis and metabolic stress, and reduce inflammatory tendon cell response. It is worth noting that the hedging immune strategy increased the secretion of Interleukin-33 (IL-33) in the damaged tendon sheath by 4.36 times, activated the mucus-IL-33-Th2 axis, and directly provided regeneration niche for the proliferation of sheath stem cells [During the remodeling stage, the collagen synthesized from the scar at the tendon decreased, and the number of blood vessels and cells produced also decreased sharply. As type III collagen is not completely remolded into type I collagen, the fibrovascular scar produced by adult tendon in the initial healing stage will never be completely replaced . The forem cells . In the em cells . An immuem cells . In addiem cells .At present, many researchers are working on patented tendon repair technology using biodegradable polymers as materials. These techniques can increase the health of tendon tissue, which can improve joint mobility and function. We conducted a comprehensive search on Google patents using the keywords “biodegradable polymers” and “tendon repair” and yielded 155 results. In a careful review, 30 techniques related to tendon repair were listed, as shown in ®-T/N in zone II flexor tendon repair, respectively, and did not obtain consistent results. Therefore, when performing tendon repair, the physician needs to consider the advantages and disadvantages of using biodegradable polymers to make the best treatment decision, depending on the specific condition and the patient’s circumstances.The effective application of biodegradable polymers in complex in vivo environments, and in particular the eventual clinical translation of the materials, still faces a number of key issues and challenges. Therefore, clinical trials of biodegradable polymers in tendon repair are summarized in ® [® [® [® is designed for type I collagen and Poly  to provide a layer between the tendon and the surrounding tissue. Its constituent ingredients are currently approved by the FDA for clinical use. The medical collagen membrane with a bilayer structure developed by GTR Bio-Tech.Co., Ltd. is purified from bovine Achilles tendon tissue and has a bilayer structure, which matches the rate of degradation to the rate of tissue regeneration after implantation and is now in clinical use [Biological scaffolds for biomedical applications are not only available for research but also have real commercial potential. Products of animal origin or products prepared from natural biomaterials of animal origin as raw materials have been approved by the FDA 510(k) for the strengthening of soft tissues. Most commercial bio-scaffolds are prepared from natural biomaterials, such as collagen , or coll® , GTR® [1® [®  and Teno® [® . The ele® [® [®  Bio-inteical use . In addiElectrospun nanofibers with controllable diameter, arrangement, high porosity, and a large surface area produced using electrospinning are usually easily able to meet the requirements of tendon repair tissue engineering, have the characteristics of low production costs and high efficiency, and are an ideal treatment choice for tendon injury ,13,14,15A 3D electrospun-nanofiber scaffold based on the controllability of the electrospinning process can better simulate the structure and shape of ECM. A 3D electrospun-nanofiber scaffold with high porosity can be manufactured using direct electrospinning, post-processing technology, and by adjusting the fiber collection technology or combining these technologies . In addiThe 3D structure of electrospun fiber provides several advantages for tendon repair, including the ability to provide a scaffold for tissue growth, support the infiltration of cells and nutrients, and be customized to match the characteristics of natural tissue. However, more research is needed to fully understand the potential mechanism of the positive effect of electrospun fibers on tissue repair. By optimizing its design and manufacturing methods, electrospun 3D scaffolds can display their capabilities in three stages of inflammation, proliferation, and remodeling after tendon injury. In the past, the use of 3D electrostatic spun wire scaffolds for tendon repair still posed many challenges. The weak mechanical properties of electrospun products prevented them from being used in hard tissue repair. The uncontrollable degradation rate of electrospun products made it a limitation in the application of regenerative medicine. However, as conventional electrospun technology is updated, there is increasingly great control over the diameter distribution of the membrane through operations such as the running track of the electrospun nozzle. At the same time, the solution concentration, electric/magnetic field, and conductivity of the solution are adjusted during the production process so that the properties of the fiber membrane are stable and controllable. In short, with the development and progress of electrospinning technology, the scalability and cost-effectiveness of electrospinning fibers used in tendon repair tissue engineering applications can be improved.


Rho GTPases family are considered to be molecular switches that regulate various cellular processes, including cytoskeleton remodeling, cell polarity, synaptic development and maintenance. Accumulating evidence shows that Rho GTPases are involved in neuronal development and brain diseases, including substance dependence. However, the functions of Rho GTPases in substance dependence are divergent and cerebral nuclei-dependent. Thereby, comprehensive integration of their roles and correlated mechanisms are urgently needed. In this review, the molecular functions and regulatory mechanisms of Rho GTPases and their regulators such as GTPase-activating proteins (GAPs) and guanine nucleotide exchange factors (GEFs) in substance dependence have been reviewed, and this is of great significance for understanding their spatiotemporal roles in addictions induced by different addictive substances and in different stages of substance dependence. The Ras-like superfamily G proteins are monomer proteins of approximately 21 kDa that function as molecular switches to regulate a wide range of primary and versatile cellular processes . There aAmong Ras-like superfamily, the Rho family (Rho GTPases) with 22 members are primary regulators of the cytoskeleton remodeling, cell adhesion, polarity, and locomotion processes . Rho GTPThe high relapse rate of substance addiction mainly lies in the fact that addiction will form lasting, stubborn and environment-related memories in the human brain. The continuous morphological plasticity of dendritic spines and the functional plasticity of excitatory synaptic transmission may be the neurobiological mechanism of the abnormal behaviors induced by addictive substances. Preliminary studies showed that Rho GTPases might participate in the acquisition and extinction of addictive substances-associated contextual memory . TherefoThe activities of Rho GTPases are mainly controlled by three classes of regulators. The first-class is Rho GTPases guanine nucleotide exchange factors (Rho GEFs). Rho GEFs are classified into two subclasses, including dedicator of cytokinesis (DOCK)-related proteins  and Dbl-Synaptic connections between neurons are crucial to all aspects of neural activity and are therefore precisely regulated. Synaptic plasticity is the activity-dependent changes in the strength and efficacy of synaptic transmission across the synapses, and these changes are thought to underlie the neurobiology of addiction .The excitatory synapses of major neurons in the brain are mostly located at the tips of dendritic spines, which are dynamic structures, and the rapid remodeling of dendritic spines is essential for synaptic formation, function, and plasticity. Inappropriate dendritic spinous morphogenesis may lead to impaired information processing in the brain. Therefore, abnormal dendritic spines are associated with many neurodevelopmental, neuropsychiatric, and neurodegenerative diseases, and dendritic spine morphology can be a proxy for synaptic strength . DendritAbnormal morphology and density of dendritic spines could be observed in patients and animals with addiction , accompaDopamine (DA) has long been considered as an important regulatory neurotransmitter, regulating salience encoding, memory expression, reward prediction, and addiction , 2021. BGrowing evidence indicated that Rho GTPases were intracellular targets of addictive substances and were involved in drug-induced dendritic spines morphogenic changes and behavior changes. After morphine conditional place preference (CPP) training, the number of hippocampal thin dendritic spines was significantly reduced, and the expression of RhoA on synapses increased, and morphine-induced CPP could be prevented by microinjection of the Rho-associated protein kinase 1 (ROCK) inhibitor H1152 to block RhoA signaling , showingPFC receives dopaminergic projection from VTA and is an important brain region in the reward circuit of drug addiction. The excitability of neurons in PFC is affected by the amplitude of action potential afterhyperpolarization, suggesting that they may be regulated by small conductance calcium activated potassium (SK) channels , which min vivo, and promote the release of cytokines and glutamate from neurons. At the same time, morphine could induce morphological changes of cultured microglia from bipolar rod-like shapes or globular to lamellipodial and flat, with membrane ruffling at the edge, which was colocalized with Rac  to regulate actin cytoskeleton remodeling in the DH and behavioral plasticity  have become fundamental molecules that control spinal morphogenesis and dendritic development . CaMKII asticity . Repeateasticity , demonstn in NAc . These r“Goal-directed” actions, the ability to choose actions based on expected consequences, are critical for the survival of individuals, which means that their performance is sensitive to the change in the connections between the action and its results. Habit-based stimulus-induced reward seeking at the expense of “goal-directed” response strategies may play an etiological role in the development and maintenance of substance dependence, especially for cocaine addiction . The corCocaine addiction leads to persistent alterations in the brain’s reward system, including increased dendrites and spine density on MSNs in the NAc and glutamatergic projection neurons in the PFC and ventral hippocampus . Except KO mice  in the cytoplasm of NAc MSNs decreased, and the level of PDZ-RhoGEF in the nucleus increased -mediated DA reuptake is one of the most critical mechanisms for substance dependence. Vav2 belongs to the VAV family with guanine nucleotide exchange activity. Compared with wild-type mice, the surface expression of DAT in the NAc of cocaine-treated Vav2 cocaine , demonstAmphetamine is a psychostimulant that can increase DA content in the synaptic cleft by inhibiting DA reuptake in dopaminergic neuron terminals, and DAT is the crucial target of amphetamine actions during addiction. Different from cocaine and other psychostimulants, amphetamine can serve as a DAT substrate to stimulate the endocytosis of DAT in the plasma membrane. For instance, after injections of amphetamine (2 mg/kg), the level of DAT on the cell membrane of the midbrain slice significantly decreased , which mSimilar to DAT, which is responsible for maintaining the DA concentration in the synaptic cleft, excitatory amino acid transporters (EAATs) are responsible for regulating the concentration of extracellular glutamate, which determines the spatial and temporal precision of glutamate neurotransmission and limits the excitotoxic effects of glutamate. EAAT3 is found predominantly in neurons and is the main subtype of glutamate transporter in dopaminergic neurons . AmphetaNAc injection of ROCK inhibitor Y27632 significantly suppressed the increase of extracellular DA levels and behaviors induced by methamphetamine (METH) . METH reThe acquisition of METH-related addiction memory increased the thin dendritic spine density of DRD1-and DRD2-MSNs and it decreased the activity of Rac1 and the expressions of its downstream p-PAK, p-Cofilin, and p-LIMK, whereas overexpression of Rac1 accelerated the extinction of METH-associated contextual memory. Additionally, although NAc microinjection of Rac1 inhibitor or activator was not sufficient to interrupt the reconsolidation of METH-associated contextual memory, the pharmacological activation of Rac1 in the NAc also promoted the elimination of thin spines and the extinction of METH-associated contextual memory. It was worth noting that Rac1 had an effect on the spine plasticity of DRD1-MSNs induced by METH, but had no effect on DRD2-MSNs. These findings indicated that Rac1 might play an opposite role in the acquisition and extinction of METH-related contextual memory, and the role of Rac1 in METH-related spine remodeling is also cell-specific, indicating that Rac1 may be a potential therapeutic target for reducing METH relapse .via activating the RhoA/ROCK pathway, and then increase the permeability of BBB  permeability, induced cytoskeleton remodeling, and reduced levels of tight junction (TJ) proteins in the hippocampus. The expressions of RhoA, ROCK, myosin light chain (MLC), p-MLC, cofilin, p-cofilin, and matrix metalloproteinase (MMP)-9 were all up-regulated, indicating that the RhoA/ROCK pathway was activated after METH treatment. After pretreatments with RhoA or ROCK inhibitors, the expressions of above-mentioned proteins significantly decreased, and the expressions of TJ proteins were increased, while the rearrangement F-actin cytoskeleton was suppressed and the permeability of rat brain microvascular endothelial cells was also reduced. These results indicated that METH could induce cytoskeleton rearrangement and TJ protein down-regulation y of BBB .The neurotoxicity caused by METH abuse is associated with neurodegenerative damage in various brain regions such as the hippocampus and dorsal striatum. For instance, METH can cause dopaminergic neurons apoptosis, and using small interfering RNA to silence ROCK2 could increase cell viabilities and reduce apoptosis of PC12 cells , showingAlcohol has been widely abused in many cultures for centuries, and drinking alcohol is related to the risk of chronic diseases including mental and behavioral disorders, liver cirrhosis, and cardiovascular diseases. Studies have found that the activity of ROCK in the striatum of rats was significantly reduced after being exposed to alcohol, while that in the hippocampus was significantly increased , indicatLow doses of alcohol  and its derivative ripasudil (Glanatec®), have been approved for clinical use. Fasudil is a small molecule ROCK inhibitor, which was first approved in 1995 in Japan for the prevention and treatment of cerebral vasospasm and subarachnoid hemorrhage  to LC and (Grant No. 82071970) to YXW, the Young Talents Project of Hubei Provincial Health Commission (Grant No. WJ2021Q053) to QR, and the Science and Technology Project of Jianghan University (Grant No. 2022SXZX25).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The collection of papers in this Special Issue entitled “Frailty in Pediatric and Young Adult Cancer Survivors: from bench to bedside” includes six interesting articles  presented by expert researchers in the fields of oncology and pediatrics. The aim of these publications is to highlight the condition—in the majority cases, very disabling—displayed by childhood cancer survivors (CCS), as well as to propose new management perspectives to ameliorate the quality of life of these subjects. One of the greatest medical successes of recent decades is certainly the improvement of the survival rate of pediatric cancer: almost the 80% of children affected by cancer become long-term survivors, achieving 5-year survival, without any administered therapy . DespiteIn particular, exposure to oncological therapies (mainly chemo- and radiotherapy) causes low-grade systemic inflammatory state onset, senescent cell accumulation, the increased production of reactive oxygen species (ROS), immune response activation and DNA mutations ,5. This Cancer therapies administered during childhood also affect human fertility, since they are responsible for direct and indirect negative effects on the gonads. In particular, in the literature, the role of alkylating agents and irradiation as the factors most responsible for a decrease in ovarian reserves is well documented . In thisCertainly, the risk of developing late effects after cancer treatments is very high, and focusing studies on related immune system alteration, oxidative stress, cell senescence, and the overall inflamm-aging process could be an appropriate strategy to predict and prevent life-threatening effects affecting CCS subjects. The papers included in this collection greatly contribute to describing the problems affecting CCS, as well as proposing some intervention possibilities, thus providing a good future perspective for the management of CCS, including many years after originally stopping therapy.


In recent years, there has been renewed interest in the maintenance of food quality and food safety on the basis of metabolomic fingerprinting using vibrational spectroscopy combined with multivariate chemometrics. Nontargeted spectroscopy techniques such as FTIR, NIR and Raman can provide fingerprint information for metabolomic constituents in agricultural products, natural products and foods in a high-throughput, cost-effective and rapid way. In the current review, we tried to explain the capabilities of FTIR, NIR and Raman spectroscopy techniques combined with multivariate analysis for metabolic fingerprinting and profiling. Previous contributions highlighted the considerable potential of these analytical techniques for the detection and quantification of key constituents, such as aromatic amino acids, peptides, aromatic acids, carotenoids, alcohols, terpenoids and flavonoids in the food matrices. Additionally, promising results were obtained for the identification and characterization of different microorganism species such as fungus, bacterial strains and yeasts using these techniques combined with supervised and unsupervised pattern recognition techniques. In conclusion, this review summarized the cutting-edge applications of FTIR, NIR and Raman spectroscopy techniques equipped with multivariate statistics for food analysis and foodomics in the context of metabolomic fingerprinting and profiling. The recent term “omic” is used in a wide variety of fields, for example, genomic, proteomic, metabolomic, amongst others. The term metabolomics can be described as the cooperation of multiple disciplines such as analytical chemistry, technology, analysis protocols and data analysis . MetabolThe current article was proposed to show the capability of vibrational spectroscopy techniques for metabolic fingerprinting by exploring previous contributions. This review article aims to explain the metabolic measurement properties of the vibrational spectroscopy techniques such as IR spectroscopy  and Raman spectroscopy. The classifications of infrared spectroscopy techniques and Raman spectroscopy were previously discussed in earlier contributions . In the Chemometrics can be defined as the statistical and mathematical methodologies employed to build experimental methodologies and reveal important knowledge from big data and deep data . The datUnsupervised pattern recognition models can be used to evaluate the connatural tendency of data without any confinements. Unsupervised methods can also be described as exploratory methods, for example, principal component analysis and hierarchical cluster analysis. These types of methodologies are usually employed to display the similarities and heterogeneities of the dataset. The most well-known and applied unsupervised chemometrics models are reported to be principal component analysis (PCA), hierarchical cluster analysis (HCA), cluster analysis (CA) and multiple correspondence analysis (MCA) .Supervised pattern recognition models have reported to require a definite training set, which is further used to predict the identity of unknown samples . In othe2 (regression coefficient), PRESS , RPD , SEP (standard error of prediction) and SECV .The calibration section is composed of a series of subheadings, such as univariate calibration, multiple linear regression, principal component regression, partial least squares and model validation  . MultivaFood recognition, classification and discrimination are highly important tasks for food integrity and food safety from farm to fork in the food supply chain. Pattern recognition techniques can be employed for a wide variety of purposes in food-related issues. These issues include food calorie estimation, quality detection of vegetables, fruits, meat and aquatic products, the determination of food contamination and sensory evaluations . Today, P. macrocarpa extracts and an effective regression model was developed using the functional groups of -CH, -NH, -COOH and -OH for the fast and reliable determination of the inhibitory activity . As. AsCaenoVarious natural and agricultural products such as essential oils, seeds, vegetables and fruits need to be explored in terms of their chemical composition. Traditional techniques, such as chromatography and mass spectrometry, have been typically used for the evaluation of the compositional properties of foods and natural products. Near-infrared spectroscopy (NIR) has been widely used for the rapid monitoring of compositional quality properties for the past 40 years . As the Saccharomyces cerevisiae. Their study showed the considerable potential of NIR spectroscopy combined with chemometrics for the discrimination and identification of different yeast strains. The authors reported VIS and NIR spectroscopy as promising techniques to screen and distinguish yeast strains with deletions in genes that disturb similar metabolic pathways. They used the spectral differences for the classification of yeast species on the basis of their metabolomes and the results were associated with the specific metabolic functions of Saccharomyces cerevisiae [2 value ≥0.97. Their results show the considerable potential of NIR spectroscopy and chemometrics for the characterization of lavender and lavandin essential oils. Additionally, the authors stated that the examination of PLS first regression coefficient helped the determination of matabolomic indicators for all lavender/lavandin varieties [Citrus species; they reported the high capability of NIR spectroscopy for the rapid quantification of various bioflavonoids through the fingerprinting capabilities of the technique. Also, they showed the potential of NIR spectroscopy combined with PLS and HCA for the discrimination of different citrus species. As can be understood from In a previous study, McLeod et al. (2009) used NIR spectroscopy combined with regression models for the prediction of biomass and chemical changes during the beer fermentation process. According to their results, good predictive results were obtained for the prediction of the ethanol concentration, specific gravity, optical density and dry cell weight, and the authors highlighted the importance of the fingerprint region . Cozzolirevisiae . Essentiarieties . In anotLi et al. (2014) developed a fast, cost-effective, and accurate NIR- and chemometrics-based methodology for the discrimination of Chinese liquors. The authors presented the results of discrimination models built using different wavelengths. The PCA-LDA, SVM and SIMCA models showed % classification ratios of 98.89, 95 and 97.22, respectively, in the spectral range of 570–1848 nm. Also, the spectral range of 1300–1848 nm yielded a classification ratio higher than 94% for all discrimination models . They obIn the last decades, there has been increasing interest in the research of metabolomics using various analytical techniques including targeted and untargeted analyses. Targeted metabolomics analysis techniques are generally used for the evaluation of a set of metabolites. Metabolomic profiling is capable of evaluating a wide variety metabolites and, generally, high-resolution chromatography techniques are used. Metabolomic fingerprinting can be used to obtain the specific fingerprint properties of biological systems, foods, agricultural products and natural products. Vibrational spectroscopy techniques, such as FTIR, NIR and Raman, provide fingerprinting information about the molecules in the composition of investigated compounds. Today, it is of great importance to acquire key information about structural ingredients to ensure the quality and safety of food and agricultural products. In this context, the application of fingerprinting spectroscopy techniques in combination with pattern recognition analyses and multivariate statistics have considerable potential as cutting-edge solutions to a wide variety of quality and safety problems in the food industry. In conclusion, this review illustrated the applications of metabolomic fingerprinting and profiling for the evaluation of various specific properties using high-throughput FTIR, NIR and Raman spectroscopy techniques combined with pattern recognition methodologies, which have been prevalent for last 15 years or so. Existing research shows the high capability of vibrational spectroscopy combined with pattern recognition analysis in determining the authenticity, quality, safety and the other essential parameters of foods on the basis of metabolomic fingerprinting. There is a need for further studies to evaluate the various challenging food safety and authenticity issues present in the food supply chain. In particular, studies presenting developments and innovations in artificial intelligence applications in this field are required as these have considerable potential for the improvement of the scientific and practical knowledge of researchers and the community.


Lipofibromatous hamartoma, first reported in 1953, is a rare, slowly progressive soft tissue tumor, the characteristics of which include the enlargement of the affected nerve via the epineurial and perineurial proliferation of adipose and fibrous tissues. Out of 200 previously reported cases of lipofibromatous hamartoma of the median nerve, there have been approximately 25 pediatric cases under the age of 18. Herein, we report a case of lipofibromatous hamatoma of the median nerve in a 3-year-old female patient who was surgically decompressed via carpal tunnel release and epineurolysis. The patient was followed-up on an outpatient clinic basis annually with sonographic evaluations, and the postoperative 10th-year follow-up did not show recurrence or any deficits in motor and sensory functions. Lipofibromatous hamartoma (LFH), first reported in 1953, is a rare, slowly progressive, benign soft tissue tumor characterized by the enlargement of the affected nerve by the epineurial and perineurial proliferation of adipose and fibrous tissues . While mWhile carpal tunnel syndrome (CTS) is the most common compressive neuropathy in the adult population, it is relatively rarely reported in pediatric populations . While CSince the discovery of LFH in 1953, there have been approximately 200 cases of LFH of the median nerve and pediatric cases . There hA three-year-old female patient without underlying diseases visited the outpatient clinic at our institution with chief complaints of an enlarging mass and discomfort of the volar aspect of the left wrist. The patient’s mother recalled no history of trauma or congenital anomalies but reported a progressively enlarging solitary mass on the wrist for the past two weeks with mild pain in the beginning. The patient was otherwise unremarkable in terms of medical conditions and was not on any medications, and her immunizations were up to date.Physical examination revealed a solitary, soft, mildly tender, palpable mass of approximately 1 × 1 cm on the center of the volar aspect of the wrist. There were no limitations in the ranges of motions of the wrist and fingers, but the patient’s agitation escalated with passive movement of the wrist joint. For this pediatric patient who still had difficulty with expressive language, it was difficult to subjectively assess Tinel’s sign, conduct Phalen’s test, or determine specific neuromuscular deficits. Gross inspection did not indicate any congenital abnormalities, such as polydactyly or café-au-lait spots.Ultrasonographic examination on the patient’s first visit to the clinic showed a severely edematous and hypertrophied median nerve from the left-wrist level down to the palm with low-echogenic intraneural multiple fascicles . In addiUpon the clinical and radiologic diagnosis of LFH, the patient was scheduled for a decompression of median nerve with a biopsy. A zig-zag incision on the volar aspect of the wrist was made from 10 cm proximal to the transverse carpal ligament down to the metacarpal joints area. Surgical exploration revealed a fusiform enlargement starting from 2 cm proximal to the transverse carpal ligament to the level of the thenar crease, surrounding the transverse carpal ligament and the median nerve . After tHistologic findings showed abundant thickened nerve bundles and accumulated fibrous and adipose tissues around the epineurium, confirming the diagnosis of lipofibromatous harmartoma in the median nerve .Postoperatively, the patient’s recovery was uneventful, without any complications of pain, discomfort, or decreased joint movement. The patient was followed-up annually with sonographic examinations of the wrist . At the Since its first report in 1953, LFH, a slowly growing soft tissue tumor, has been reported in 25 pediatric cases of median nerve involvement . The preIn the diagnosis of LFH, MRI plays a critical role by revealing pathognomic radiologic features and low-intensity serpentine nerve fibers embedded in abundant high-intensity adipose and fibrous tissues, also known as “cable-like appearances” . In addiRegarding the treatment of LFH, there is no standard treatment consensus, and patient management varies depending on the extent of the soft tissue lesion . HistoriIt is critical to consider a patient’s history, physical examination findings, and radiologic assessment data all together before making a decision on surgical treatment. As seen in the current case, when the patient is at the toddler age and incapable of expressive language, the clinical assessment of certain signs and symptoms is often limited and challenging, even in postoperative follow-ups. Furthermore, as it is a rare entity, it is difficult to compare various surgical techniques in terms of their effectiveness in treating LFH with a long-term follow-up. The currently available literature on pediatric LFH lacks long-term follow-up outcomes, and the corresponding cases are mostly followed-up for less than a few years. Therefore, the current case report provides valuable clinical and radiologic outcomes without tumor or symptom recurrence through annual follow-ups conducted consecutively for 10 years. Over the 10-year postoperative period, the patient was able to maintain intact motor and sensory functions without any pain or discomfort after the performed nerve decompression with the carpal tunnel release and epineurolysis of the median nerve.Due to the rarity of LFH, a precise understanding of its epidemiology, treatment, and prognosis has been limited in the previous literature. The current case of LFH of the median nerve is the first to be reported in South Korea, and the high index of clinical suspicion for LFH is imperative, especially in pediatric carpal tunnel syndrome. Even though very little is known about the predictive prognostic values of surgical techniques in this regard, 10-year consecutive follow-ups of an initially 3-year-old patient with LFH showed satisfactory clinical outcomes after decompression with carpal tunnel release and epineurolysis. Furthermore, increased multidisciplinary clinical awareness of the tumorous condition is critical for best-practice management.


Hypergraphs have become an accurate and natural expression of high-order coupling relationships in complex systems. However, applying high-order information from networks to vital node identification tasks still poses significant challenges. This paper proposes a von Neumann entropy-based hypergraph vital node identification method (HVC) that integrates high-order information as well as its optimized version (semi-SAVC). HVC is based on the high-order line graph structure of hypergraphs and measures changes in network complexity using von Neumann entropy. It integrates  As an interdisciplinary research field that encompasses big data, machine learning, graph theory, and other related disciplines, network science  providesA close correlation exists between centrality issues and the recognition of significant nodes, whereby nodes with greater centrality are generally deemed to hold greater importance and tend to have greater influence for information propagation  within aSo far, scholars have conducted related research on the task of mining important nodes in hypergraphs, and have proposed some classical methods such as hyperdegree centrality  (HDC), cMeanwhile, hypergraphs, which accurately and naturally express interactions that go beyond pairwise interactions between entities in complex systems, make the importance of high-order coupling relationships in networks evident. The introduction of high-order information provides new ideas and challenges for research on identifying vital nodes in hypergraphs. To address this, we propose a hypergraph node identification method that integrates higher-order information: high-order von Neumann entropy centrality (HVC). The proposed method captures high-order information through hypergraph high-order line graphs and uses the variation of von Neumann entropy to measure changes in the network’s complexity. The more drastic the change, the greater the impact of the node on the network’s complexity and the more important the node is. At the same time, to balance the complexity and accuracy of the method, we proposed semi-quadratic approximate von Neumann entropy centrality (semi-SAVC) by using quadratic approximations of von Neumann entropy and some high-order information. The performance of the proposed method was comprehensively evaluated using empirical hypergraph datasets from the perspectives of nonlinear propagation influence, robustness, correlation, and monotonicity. We found that the high-order line graph information showed a saturation effect in the task of identifying vital nodes in hypergraphs.The rest of this paper is organized as follows. The concept of hypergraphs was first introduced by Berge . A hyperFor The sub-hypergraph  H′=V′,E′In a hypergraph, the ne graph  LsH of hThe concept of von Neumann entropy  original systems , which iHDC: Hyperdegree centrality  measuresCC: The closeness centrality  emphasizVC: The vector centrality  of hyperSHC: Sub-hypergraph centrality  characteIn the subsequent experiments, we chose HDC, CC, VC, and SHC as the baseline methods for comparison. On the one hand, these classical methods have been widely accepted and used in identifying important nodes in hypergraphs, and the comparison of multiple methods can enhance the rigor of the experiment. On the other hand, the four methods approach the problem from different perspectives, which can better highlight the advantages of the proposed method in a comprehensive way.Higher-order information and von Neumann entropy in networks were the focus of the research in this paper. We believe that the incorporation of higher-order information will have a positive effect on identifying important nodes in hypergraphs. Moreover, as suggested in Step 1: For a hypergraph Step 2: The change in von Neumann entropy for each The greater the value of Step 3: Based on the cardinality of hyperedges Step 4: High-order information of hypergraph is fused, thus finally obtaining the high-order von Neumann entropy centrality:In the HVC, incorporating high-order information leads to an increase in method complexity. Considering the limitations of the complexity of von Neumann entropy itself, we proposed the semi-quadratic approximate von Neumann entropy centrality (semi-SAVC) approach. The process is similar to the HVC, but differs in that, in Step 2, which only calculates the change in von Neumann entropy of the ficiency . Furtherficiency , which iVon Neumann entropy mainly involves solving the problem of matrix eigenvalues and eigenvectors, so calculating the von Neumann entropy requires In this section, we introduce the hypergraph datasets used in the subsequent experiments, which are empirical data from multiple domains. Each dataset has different topological properties, as shown in The Erdos971 dataset was sourced from the famous Pajek dataset . BatagelNext, a detailed analysis of the s-overlap between hyperedges in each dataset was conducted. As shown in The dynamics of hypergraph propagation provide a solid theoretical foundation to evaluate the identification methods of vital nodes However, existing hypergraph propagation models such as SIS , SIR 4242, and tThis paper employed a nonlinear propagation evaluation method based on the SIR model of hypergraphs to assess its effectiveness. The nodes in the network have three states, namely susceptible (S), infected (I), and recovered (R); for simplicity, the infection process was modeled nonlinearly while the recovery process was modeled linearly, the specific process is as follows: (I) Select seed nodes based on demand and place them in the I state; (II) At each time step, S state nodes have a probability of Utilizing hypergraph nonlinear propagation, the propagation influence of nodes in different methods serves as compelling evidence for effectiveness. Node influence is measured by the total proportion of I and R state nodes in the network at time step As indicated in ficiency  E in theriangles , and theDuring the propagation process, the adjustable parameters In addition, we observed that in the Restaurant dataset, the influence variations of the HVC and semi-SAVC were similar, but they were distinguishable in the other datasets. This raised our attention. Since the semi-SAVC used a quadratic approximation of von Neumann entropy, it incurred a loss in accuracy. However, its propagation results remained comparable to that of HVC. Could it be that the semi-SAVC adoption of a high-order line graph resulted in an increase in identification accuracy despite halving its order? This led us to the association with the existence of the saturation effect of network information ,49. To iIn the previous section, the effectiveness of the proposed method was verified through a hypergraph nonlinear propagation model. To further investigate the correlation between identification results from different methods, the Pearson correlation coefficient  was intrFirstly, it can be observed that there was consistently high correlation between the HVC and semi-SAVC in most hypergraphs. Additionally, the results in Network robustness is a fundamental way to measure the effectiveness of vital node identification methods . It aimsFirstly, it can be observed that in the six hypergraphs, the difference in the largest component size between different methods was not significant when the top 10% nodes were removed. As the removal proportion increased, larger differences tended to occur. This was determined by the multi-body interaction characteristic of the hypergraph, which has a stronger resistance to isolated nodes compared to complex networks. Meanwhile, in the vast majority of hypergraphs , after removing the top 10%, 20%, and 30% ranked nodes, semi-SAVC and HVC always had the minimum component size, indicating that the top-ranked nodes had a more significant impact on network connectivity and highlighting the effectiveness of the proposed method. In addition, we also found that the changes in the largest component size after removing different proportions of nodes using different methods were extremely similar in the Geometry and Film-ratings hypergraphs. This may be closely related to the network structure. As shown in An effective method for identifying important nodes should not only guarantee the accuracy of the identification results but also emphasize the discriminability of the outcomes. Therefore, we introduced the monotonicity index , which iIn this article, we proposed a node identification method (HVC) as well as its optimized version (semi-SAVC). HVC is based on the high-order line graph structure of the hypergraph, which measures the change in network complexity using von Neumann entropy and quantifies node importance in the hypergraph by mapping hyperedges to nodes, incorporating In the six empirical hypergraphs, we compared the performance of the proposed node identification methods from the perspective of propagation influence, correlation, robustness, and monotonicity by evaluating them comprehensively with four baseline methods. Firstly, in the influence evaluation of the methods, we used the latest hypergraph nonlinear propagation model to investigate the relationship between the influence (the proportion of infected and recovered nodes) and time steps. The experimental results showed that the proposed methods always maximized the influence compared to the baseline methods, proving their effectiveness. Meanwhile, we also investigated the influence of adjustable parameters and nonlinear indices in nonlinear propagation on the influence of top-ranked nodes by different methods, and found that both promoted the nonlinear propagation of the hypergraph. In addition, inspired by the above experimental results, we explored the impact of the order of the Although our work provides some reference value for vital node identification in hypergraphs, this direction still has huge potential. With the development of deep learning technology, the introduction of graph structures and related algorithms in neural network models, graph neural networks  have eme