Violence against women research largely excludes transgender women’s experiences and violence from perpetrators other than intimate partners. This study compares patterns of violence exposure among cisgender and transgender female sex workers (FSWs) and the associations with syndemic health outcomes. We used cross-sectional surveys from samples of cisgender and transgender FSWs living with HIV in the Dominican Republic . We used latent class analysis to identify patterns of emotional, physical, and sexual violence and harassment by partners, clients, and police. We assessed sociodemographic and occupational predictors in relation to class membership, and class membership in relation to health , using logistic regression. Two classes were identified in cisgender sample: Low Reported Violence Exposure (Class 1) and Sex Work-related Police Harassment (Class 2). Class 2 participants had greater odds of scoring abnormal or borderline abnormal anxiety on the Hospital Anxiety and Depression Scale (HADS-A) , moderate-to-severe depression per the Patient Health Questionnaire-9 (PHQ-9) , and any illicit drug use in the past six months , compared to Class 1. The transgender sample produced three classes: Low Reported Violence Exposure (Class 1); Sex Work-related Police Harassment (Class 2); and Sex Work-related Violence and Harassment (Class 3). Class 3 participants had greater odds of having anxiety  and depression , while Class 2 participants had greater odds of perfect ART adherence during the previous four days , compared to Class 1. The more diverse and extreme violence patterns uncovered for the transgender sample show this group’s heightened risk, while similar patterns across groups regarding police abuse highlight a need for police-focused violence prevention interventions. Each sample’s highest violence class was associated with poor mental health, underscoring the need for mental health interventions for all FSWs. Globally, sex workers experience a disproportionate burden of violence compared to the general population –6. SociaIn the Dominican Republic (DR), no law explicitly relates to a consenting adult aged 18 years or older engaging in sex work, making it de facto legal; there are laws, however, that restrict proxenetismo, which is when someone benefits financially from the exploitation, commercialization, or defrauding of another person in a sexual manner, and sex work by minors , 21. TheGlobally, FSWs are also at risk for and experience epidemics of HIV, substance use, and poor mental health that constitute a syndemic –29, resuDespite differences in risk and experiences of violence for cisgender and transgender FSWs , 14, 15,A gap exists in the current literature regarding typologies of violence experienced by transgender FSWs and how the transgender-specific typologies of violence exposure compare to those of cisgender FSWs. This study expands upon the violence against women (VAW) research cannon to identify and assess patterns of different forms of violence perpetrated by various actors experienced by cisgender and transgender FSWs living with HIV, specifically in the DR. To support the comparison between cisgender and transgender FSWs, we were guided by Intersectionality, a theory that acknowledges how people’s experiences, opportunities, and outcomes are informed by multiple systems of power and oppression that intersect in additive or compounding ways . FurtherWe sought to answer the following questions: 1) what do patterns of violence from various perpetrators look like for cisgender and transgender FSWs?; 2) what factors are associated with risk of different patterns of violence exposure?; and 3) what is the relationship between different patterns of violence exposure and various health outcomes? We hypothesized that class structures would differ for cisgender and transgender FSWs; that sociodemographic and occupational factors would be associated with class membership; and that more severe patterns of violence exposure would be associated with poor HIV continuum of care, mental health, and substance use outcomes.This study used two companion studies with cisgender and transgender FSWs living with HIV in Santo Domingo, DR. The parent study was prospective with three waves of data collection with cisgender FSWs in the DR as well as Tanzania ; the supFor the cisgender dataset, an existing cohort of FSWs from Abriendo Puertas, a multi-level intervention detailed elsewhere –43, was For the transgender dataset, the same recruitment procedures were used led by FSW peer navigators re-engaging participants from an pilot adaptation study of the Abriendo Puertas intervention . Data coAll data collection was conducted in Santo Domingo, the capital of the DR, at the Instituto Dermatologico y Cirugia de la Piel (IDCP). All participants completed a survey of demographic, behavioral, and socio-structural factors. Further, a blood sample was collected for HIV viral load testing using polymerase chain reaction testing .Both studies were reviewed and approved by the Johns Hopkins University (JHU) Bloomberg School of Public Health Institutional Review Board (IRB) and the IDCP. The George Washington University IRB deferred to the JHU IRB. Participants verbally consented to participate as approved by the JHU IRB and the IDCP. Participants were compensated for their time with $10 USD (paid in DR pesos).Seven items capture participants’ experiences of violence –48. ThesSocio-demographic variables. These include: 1) age; 2) educational attainment based on the last grade completed by school level; 3) average monthly income from all revenue sources in the past six months; and 4) relationship status .Occupation variables. These include: 1) traveling outside of the city where they reside to exchange sex for money in the past six months (yes versus no); 2) the average number of weekly clients over the past six months; 3) being drunk or high while exchanging sex for money (ever versus never); 4) where they most often meet clients ; and 5) where they most often go on dates with clients . For the last two predictors, participants could select as many response options as necessary. Dichotomous variables were created for informal establishments only versus any formal establishments. For where participants meet clients, formal establishments include bars/clubs, hotel/guesthouse, and restaurants; informal establishments include private parties, on the street/park/outside, via mobile phone, corner stores, liquor stores, and car washes. For where participants go on dates with clients, formal establishments include bars/clubs and hotel/guesthouse; informal establishments include private parties, private vehicle, client’s house, participant’s house, other private house, and the street/park.HIV continuum of care. These include: 1) Viral suppression: defined as <400 copies/mL versus ≥400 copies/mL [opies/mL ; 2) CurrMental health. These include: 1) The anxiety-specific module from the Hospital Anxiety and Depression Scale (HADS-A), a 7-item scale, was utilized to assess symptoms of anxiety. The variable was categorized as Normal (score of 0–7) versus Borderline Abnormal or Abnormal (score of ≥8) [e of ≥8) . 2) The e of ≥8) .Substance use. These include: 1) The Alcohol Use Disorder (AUD) [er (AUD)  measure Descriptive analyses were conducted for sociodemographic variables, occupational characteristics, and violence exposures. T-tests and chi-square statistical tests were conducted to compare the variables between the cisgender and transgender samples.LCA was conducted within each group of participants to identify typologies of violence exposure. Additional classes were added to the model until fewer than five percent of participants were assigned to any given class. We used the following criteria to determine the best fitting number of classes: Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and sample size-adjusted BIC (aBIC) ; Vuong-Lo-Mendell-Rubin Likelihood Ratio Test (VLMR-LRT) and Bootstrapped Likelihood Ratio Test (BLRT) ; and entropy (greater than 0.70), as well as the meaningful conceptual interpretation of the latent classes –55. We rWe assessed the relationship between predictors and class membership by conducting logistic regression or multinomial logistic regression, depending on the number of classes in the final models, using the three-step procedure in Mplus. To be parsimonious, the predictors with crude odds ratios with p-values<0.10 were included in the multivariate model.Finally, we conducted logistic regression or multinomial logistic regression in Stata, depending on the number of classes, to examine the association between class membership and each syndemic health outcome, without and then with covariates that differed across classes. We conducted additional post-hoc regression analyses to examine potential syndemic-related explanations for individual health outcome results.The descriptive analyses and outcome-related logistic regressions were conducted in Stata version 16.1 . The LCAFor occupational characteristics, a larger proportion of transgender participants traveled for sex work  and were ever drunk or high while exchanging sex for money  than their cisgender counterparts. They also had more clients per week than the cisgender participants .More cisgender FSWs were virally suppressed  and currently taking ART  compared to the transgender FSWs. Further, a larger proportion of cisgender participants reported ART disruption in the past six months compared to their transgender counterparts . A larger proportion of transgender FSWs reported any illicit drug use in the past six months compared to the cisgender FSWs .For violence exposure, transgender FSWs reported more physical and/or sexual violence from new clients , regular clients , and police  than the cisgender FSWs. Further, more transgender participants reported verbal harassment  and physical and/or sexual harassment  from police compared to the cisgender participants.The two classes are interpreted as Low Reported Violence Exposure (86.30% of participants) and Sex Work-related Police Harassment (13.70%). We defined and compared violence exposure patterns for cisgender and transgender FSWs and uncovered unique relationships between these group-specific violence exposure typologies and other syndemic health outcomes. While we found similarities between the two groups, suggesting that the shared intersecting systems of oppression they face—sexism, sex work-related stigma, and HIV-related stigma—inform the types and severity of violence exposure, concrete differences highlight how transphobia informs greater risk for transgender FSWs in the DR.The frequencies for each violence item show that transgender FSWs experience more violence than their cisgender counterparts, which mirrors past research –60. WhilThese models support existing evidence that transgender women in the DR face systemic gender-based violence (GBV) partly due to transphobia , 61–63. Another important finding from both the cisgender and transgender models is the prominent role of police in creating an unsafe environment for FSWs. While sex work in the DR is not illegal for consenting adults, which all participants were, reports show that police routinely harass, rob, and abuse sex workers with no legal cause , 66. TheOne possible explanation for the configuration of Sex Work-related Violence and Harassment class from the transgender model, which shows high probability of experiencing physical and/or sexual violence from new and regular clients in addition to all forms of harassment and violence from police, is how police behavior can impact FSWs’ work decisions and the implications for violence exposure. Shannon et al.  reportedThis study has important implications for violence prevention among FSW. Violence prevention interventions are needed in the DR to change police engagement with FSWs. Work in India under the umbrella of the Avahan program, which was launched as a 10-year initiative to change the course of the HIV epidemic in India , offers Beyond the direct impact of violence, we must consider the broader role of harassment and violence on syndemic health outcomes. We found that being assigned to the respective class with the greatest violence exposure pattern increased the odds of both cisgender and transgender FSWs scoring Borderline Abnormal or Abnormal on the HADS-A and having moderate to severe depression based on the PHQ-9. Exposure to violence from intimate or regular partners, clients, police, and others is significantly and directly associated with poor mental health outcomes for FSWs around the world , 75–79. Additionally, being in the Sex Work-related Police Harassment class was significantly associated with HIV continuum of care for both groups, though not entirely as expected. For the cisgender sample, being in the Sex-work Related Police Harassment class was marginally associated with greater odds of ART disruption in the past six months. This finding mirrors past research that shows police harassment, and GBV more broadly, can impede successful HIV treatment among sex workers , 80–82. In contrast, the association between violence and HIV care for the transgender sample was the opposite of what was expected based on the existing research and compared to the cisgender sample. Transgender participants assigned to their respective Sex Work-related Police Harassment class had significantly greater odds of perfect ART adherence during the previous four days. It is possible that the fact that the transgender women were recruited for this study in part through HIV clinics and by peer navigators from a pilot intervention focused overall on improving HIV care and treatment helps explain this result . HoweverIn addition to considering how violence exposure patterns relate to syndemic health outcomes, we identified significant predictors of class membership. The only consistent predictor variable for both groups was traveling to exchange sex for money, which increased the odds of being in each group’s respective highest violence exposure class. Sex work-related mobility is often framed as a risk factor, as it has been found to increase FSWs’ odds of experiencing violence as well as increasing the severity of violence , 88. MobA consistent divergence found between the cisgender and transgender samples, for both predictors of and outcomes associated with class membership, relates to substance use. For the predictors, ever being high or drunk while exchanging sex for money was significantly associated with being in the respective highest violence exposure class, but only for the cisgender FSWs. For the outcomes, being in the sample-specific highest violence exposure class was associated with greater odds of illicit drug use in the past six months, but, again, only for the cisgender FSWs. These results from the cisgender sample mirror existing research that shows that substance use while working increases the odds of experiencing violence from clients and police –92 and vFor the transgender sample, the lack of significant associations with both variables related to substance use is unexpected based on this existing literature connecting sex work, substance use, and violence victimization , 90–94. Regardless of the differences found between the samples, the combination of high reported substance use among transgender FSWs and significant differences in substance use based on violence exposure patterns for cisgender FSWs highlight the need for interventions related to substance use among all FSWs. Existing research shows that FSWs’ inability to access substance use treatment is significantly associated with different forms of GBV, including violence and harassment from clients and police , 97. PurDespite the strengths of using LCA, comparing cisgender and transgender FSWs, and including multiple violence and harassment items, this study has limitations. One is the use of cross-sectional surveys. Another is the relatively small non-representative sample sizes, which means the results are not generalizable. The sample sizes were calculated for the primary research questions, not for conducting a LCA. Concerns about power may exist, particularly when examining the transgender sample, which only has 100 participants. However, we limited the number of items included in the model as smaller sample sizes may be adequate for models with fewer items and classes . FurtherFurther, this secondary analysis draws from two studies that were not specifically designed to examine experiences of violence among FSWs. There may be other forms of violence that FSWs experience or nuances regarding those experiences  that are missing. Additionally, a skip pattern in the survey led to only participants that reported having specific partner types in the previous 30 days being asked about physical and sexual violence related to those types of partners in the past six months. This skip logic, combined with the fact that intimate partner violence and sexual violence are often underreported , 101, meAdditionally, differences between the cisgender and transgender FSWs are ascribed to transphobia, yet we do not include any measures of transphobia in the analyses conducted. Rather, we assume that systemic oppression based on transgender identity is a key driver of the differences found between the two groups of women given the overlap they share on the other forms of systemic oppression that could otherwise explain differences in violence exposure, i.e. sex work-related stigma, HIV-related stigma, and sexism. Intersectionality helps us understand the differential impact of transphobia on the experiences of oppression and marginalization for transgender and cisgender FSWs. We, however, did not conduct an intersectional analysis; this would be a valuable pursuit for future research. It is also possible there are other aspects of systemic oppression at play that are not considered or measured in this analysis. Finally, we utilize a syndemic framework to consider various health outcomes and how they may interact with each other, but we do not conduct a syndemic analysis. Instead of testing disease interaction , 103, weThis study presents a nuanced understanding of the nature of violence exposure for FSWs living with HIV in the DR and illuminates how transphobia informs violence severity for cisgender and transgender FSWs differently. Further, police were identified as key perpetrators for both groups, suggesting that interventions targeting police interactions with FSWs are needed as these state actors significantly impact different syndemic health outcomes for both cisgender and transgender FSWs. Finally, more extreme patterns of violence for each group were significantly associated with anxiety and depression, which signals a need for greater investment in mental health care for the entire FSW community.


This Special Issue of Nutrients, “Influence of Maternal Diet and Environmental Factors on Fetal Development”, requests articles on the roles of maternal diet and environmental factors such as microbiota, plastics, and endocrine disruptive chemicals impact fetal development.The maternal diet is critically important before and during pregnancy for the optimum development of the fetus . The preMaternal n-3 and n-6 long-chain polyunsaturated fatty acids status are essential to fetoplacental growth and development ,7,8,9,10Various environmental chemicals, including endocrine-disrupting chemicals (EDCs), can alter the cellular differentiation process and epigenome during the developmental stages in the fetoplacental axis . ExposurDuring pregnancy, the composition of the maternal gut microbiota and changes have significant consequences for fetal development and adult health . Gut micThe maternal nutritional and environmental factors can alter the epigenetic state of the fetal genome and imprint gene expression . EpigeneThis Special Issue invites articles on maternal nutrients, environmental factors, and their impacts on fetal and neonatal development and adult health. In addition, articles are invited on the maternal dietary factors and other potential modulators of the maternal–fetal microbiota axis during pregnancy, impacting offspring’s microbiota and health.


The contributions in this Research Topic focus on the recent advances in autism research by exploring recent trends and findings, especially in diagnosis, monitoring, intervention, analysis, therapy, interaction, and training. Most of the studies presented in this Research Topic examine and highlight the importance of incorporating technologies, such as robots, and techniques to support the diagnosis and therapy of individuals with autism.Digitally assisted diagnostics of autism spectrum disorder,” and authored by Koehler and Falter-Wagner, explores the potential of digital technologies in improving the diagnostic of autism by providing objective and evidence-based decisions. While the article highlights the benefits of using artificial intelligence combined with automated techniques to identify cognitive, behavioral, and neuronal symptoms, however, it stresses that digital technologies should not replace, but instead complement clinical decision-making by accounting for the complexity and uniqueness of individuals with autism spectrum.The first article in this Research Topic, titled “Randomized controlled pilot study of an app-based intervention for improving social skills, face perception, and eye gaze among youth with autism spectrum disorder,” and authored by Chung and Chung, presents and examines the potential of using an app-based intervention aimed to improve social skills, eye gaze, and facial perception in children with autism. The outcomes of this work highlight the effectiveness of the proposed app-based intervention as demonstrated by the improvements in social skills, face perception, and eye gaze.The second article, titled “Li et al., titled “Integrated analysis of endoplasmic reticulum stress regulators' expression identifies distinct subtypes of autism spectrum disorder,” investigates the potential and patterns of endoplasmic reticulum stress regulator in autism. Based on machine learning techniques, the study was able to identify and classify individuals with autism based on their expression profiles. The analysis conducted in this study revealed insights about the stress regulators and highlighted their role in individuals with autism.The third article by Comparing the effectiveness of robot-based to human-based intervention in improving joint attention in autistic children,” by So et al., compares the learning effectiveness of robot-based intervention in improving joint attention in children with autism as compared to human-based intervention. The outcomes reveal the potential of considering robot-based intervention in supporting joint attention and social communication skills.The fourth article, titled “Global trends and hotspots in the digital therapeutics of autism spectrum disorders: a bibliometric analysis from 2002 to 2022,” authored by Wu et al., examines the contemporary global digital therapeutics status pertaining to autism research. The article highlights trends incorporating cutting-edge technologies and techniques, such as virtual reality and machine learning, in the development of digital therapeutics for individuals with autism.The fifth article “Takata et al., and titled “Social skills training using multiple humanoid robots for individuals with autism spectrum conditions,” investigates the effectiveness of using multiple humanoid robots to develop a training program to target social skills in individuals with autism. The findings of this work showed the potential and effectiveness of using humanoid robots to support social skills in autism therapy for individual with autism.The sixth article by Development and adaptation of a strength-based job interview training tool for transition age youth on the autism spectrum using community engaged methods,” and authored by Genova et al., evaluates the feasibility of a job interview training tool aimed to assist adults with autism with interviews. Based on the strength approach, the findings highlight the acceptability, accessibility, and usability of this tool to support showing their strengths and skills in job interviews.The final article, titled “We hope this Research Topic will provide the reader with insightful findings and trends about the recent technological and tools advances in autism research.AA: Writing – original draft, Writing – review & editing. W-CS: Writing – original draft, Writing – review & editing. J-JC: Writing – original draft, Writing – review & editing. AB: Writing – original draft, Writing – review & editing.


Technological progress in digital therapeutics—and, in particular prescription digital therapeutics (PDTs)—has outpaced the processes that the Food and Drug Administration (FDA) uses to regulate such products. Digital therapeutics have entered the health care ecosystem so rapidly that substantial misunderstandings exist about how they are evaluated and regulated by the FDA. This review briefly explains the relevant regulatory history of software as medical devices (SaMDs) and reviews the current regulatory landscape in which prescription and non-prescription digital therapeutics are developed and approved for use. These are important issues because PDTs, and digital therapeutics in general, are an explosively growing field in medicine and offer many advantages over conventional face-to-face treatments for the behavioral dimensions of a wide range of conditions and disease states. By allowing access to evidence-based therapies remotely and privately, digital therapeutics can reduce existing disparities in care and improve health equity. But clinicians, payers, and other healthcare stakeholders must appreciate the rigor of the regulatory frameworks within which PDTs are approved for use. As in practically every other sphere of life, medicine in the past two decades has become ever more digitized. At every level, from the conduct of wholly remote digital clinical trials to the use of digital diagnostic tools and, increasingly, the use of digital therapeutics (whether prescription or non-prescription) to treat serious disease states, digital technologies are transforming healthcare. The expanded use of digital therapeutics has been fueled by the ever-increasing prevalence of chronic or difficult-to-treat conditions such as mental health conditions, substance use disorders, insomnia, and lower back pain as well as by acute shortages of providers who are skilled in delivering the behavioral therapy components of care that are so often critical to patient recovery.But, in part because of the speed with which prescription digital therapeutics (PDTs) have entered the health care ecosystem, some uncertainty exists about how rigorously these devices are evaluated and exactly how they are currently regulated by the Food and Drug Administration (FDA). Torous et al., recently outlined how regulatory approaches can improve innovation in digital devices . This peThe 1976 Medical Device Amendments to the Food, Drug, and Cosmetic Act requires that FDA regulate products intended to diagnose, treat, and/or manage disease. After 1987, FDA was fully aware of the potential role of computers and software in healthcare when it published its “Draft Policy on the Regulation of Computer Products.” This document provided guidelines about which software products were regulated as medical devices and which were exempt from regulatory controls such as premarket notifications. Specifically, the guidance stated that the following software was not subject to registration, listing and premarket notification : (1) general purpose articles, 2) computer products manufactured by licensed practitioners for use in their practice (3) computer products used in teaching and non-clinical research, and (4) computer products which provide opportunity for competent human intervention. The guidance further stated that the following computer products would require notification to FDA prior to marketing: (1) computer products excluding competent human intervention and (2) substantially equivalent computer products. Computer products that do not meet any of the other criteria would be subject to premarket approval . A 1989 draft policy statement, “FDA Policy for the Regulation of Computer Products,” reiterated the 1987 draft and was the agency's operational policy for almost 20 years  guidance document published in 2013 and updated twice in 2019  was created within the Center for Devices and Radiological Health (CDRH) to lead efforts to catch up with the digital revolution . The DHCThe FDA currently regulates digitally-delivered treatments that meet the definition of software as a medical device (SaMD) . SaMD isSaMD products, like all medical devices, are evaluated for their perceived potential risk to patients and are assigned to one of three classes: Class I (low risk); Class II (moderate risk); and Class III (high risk) . Class IAlthough the first FDA-authorized PDTs were authorized as Class II devices based on their indications  , differeImportantly, Class II devices generally include special controls. For example, FDA might specify requirements around labeling or clinical data to satisfy questions of safety and effectiveness . Some ex•de novo pathway, which requires clinical data demonstrating the safety and effectiveness of the device (The e device . Devices•de novo or another 510(k) pathway (The 510(k) clearance pathway, which requires the submission of clinical data demonstrating substantial equivalence in terms of safety and effectiveness to a predicate product authorized either via the  pathway .Both pathways involve the submission of detailed data reports and product descriptions that inform the creation of patient and clinician labeling/instructions for use if the product is authorized.Once any kind of digital treatment has been evaluated in one or more clinical studies  the data and formal requests for authorization are submitted via one of two FDA pathways, each with regulatory and evidence-based requirements:Work is underway to create a dedicated FDA regulatory framework for SaMD products such as PDTs that reflects the unique attributes of these devices. For example, unlike pharmaceuticals, SaMD products can be frequently updated following FDA authorization, and products relying on artificial intelligence as a component of treatment may “learn” or change how their algorithms perform over time.In 2017, the FDA announced the Software Precertification Pilot Program, which, it is hoped, will provide more streamlined and efficient regulatory oversight of software-based medical devices developed by manufacturers who have demonstrated a robust culture of quality, organizational excellence, and willingness to monitor their products once they reach the market. Nine companies have participated in the pilot program and have committed to reviewing real-world performance of their products to ensure patient safety and product quality .The proposed approach looks first at the digital health technology developer, rather than solely at the product, which is the current focus of traditional medical device regulations. The new processes seek to accommodate the rapidity with which software products can respond to glitches, adverse events, and other safety concerns. In the Pre-Cert program, the FDA is proposing that software products from authorized companies would continue to meet the same safety and effectiveness standard that the agency expects for products that have followed the traditional path to market. FDA released a final report on this program in September 2022 . The repDigital treatments, like other therapeutic products, may be prescription or non-prescription. Prescription products require initiation by a licensed healthcare professional, as governed by state-level health authorities. The stipulation for prescription is based on review of the product and a variety of factors by FDA. Prescriptions may be required for the treatment of serious disease, the use of higher-risk devices, the need for a secure diagnosis by a trained clinician, monitoring and follow-up to determine appropriate response, and/or to compare treatment options to determine optimal treatment approaches.PDTs are software-based treatments delivered on smartphones or tablets that address the behavioral dimensions of many diseases and conditions . The firde novo pathway as a Class II device, while another non-prescription menstruation tracker, Clue, was authorized via the 510(k) pathway using Natural Cycles as a predicate device  review and provide input, even if CDRH was the primary review center (In some cases, PDTs may be intended to be used alongside standard of care pharmacotherapy. In such cases, such as reSET-O®, which is intended to be used alongside the pharmacotherapy buprenorphine, both FDA's CDRH w center . We are FDA has recognized for decades that software is not risk free. Software can result in adverse events, mistreatment, lack of treatment, or other errors across many disease areas , 30. It The Pre-Cert program and the Digital Health Center of Excellence mentioned previously are examples of the kinds of changes that can create FDA regulatory frameworks aligned with different product types to improve transparency, clinical responsibility, authorization efficiency, and clear labeling for stakeholders. The rise of FDA-regulated digital therapeutics has spurred regulatory evolution and provides experience to support further refinement and richness in FDA regulatory frameworks that balance risk and speed of bringing effective treatments to market, while maintaining public health. FDA, policymakers, research experts, and developers, must work together to make FDA policies related to digital therapeutics as nimble, flexible, and dynamic as the technologies themselves. However, reasonable and flexible regulation only works with responsible enforcement by FDA and compliance by the industry.


This article presents an overview of the pain research programs within the National Institutes of Health (NIH) Helping to End Addiction Long-term® Initiative, or NIH HEAL Initiative®. Launched in 2018 to address the opioid crisis, the NIH HEAL Initiative supports research on addiction prevention and treatment. A key component of addiction prevention is the development of new, effective, non-addictive treatments for acute and chronic pain. HEAL's innovate research portfolio spans the spectrum from therapeutic discovery and development through clinical trials and into clinical practice. Chronic pain is a significant public health concern affecting approximately 20% of adults in the United States. Approximately 4% of these individuals experience high impact pain that interferes substantially with major activities. Research and clinical experience have contributed to a continuously evolving understanding of pain. Historically, pain was initially considered to be associated with tissue damage, but current concepts incorporate the appreciation of pain as a biopsychosocial phenomenon . The IntThe National Institutes of Health (NIH) Helping to End Addiction Long-term® Initiative, or NIH HEAL Initiative®, was launched in 2018 during a critical period in which the intersection of the opioid crisis and recognition of pain as a major public health challenge indicated that developing new options for pain management was a crucial element of fighting the opioid crisis. The HEAL Initiative applies a scientific approach to fund research to develop and implement non-addictive, effective pain mitigation strategies.The nation's focus on pain management as a public health strategy dates back to the passage of the Patient Protection and Affordable Care Act (ACA) of 2010. This law identified the need for pain research and treatment and commissioned the National Academy of Medicine  to hold a conference to “increase the recognition of pain as a significant public health problem in the United States.” The resulting conference and 2011 IOM study committee report “Relieving Pain in America: A Blueprint for Transforming Prevention, Care, Education, and Research” identified the need for a cultural shift in how pain is understood, prevented, and treated. To enhance research efforts and to promote collaboration in pain research and treatment, the ACA also established the Interagency Pain Research Coordinating Committee (IPRCC), which includes representatives from government agencies, non-governmental research entities, healthcare organizations, providers, and patient communities. In response to the IOM report, NIH and the IPRCC analyzed the existing federal pain research portfolio, convened expert panels of working groups and consultants, and developed the National Pain Strategy (NPS) in 2016 and the National Pain Research Strategy (NPRS) in 2017. These initiatives identified gaps in pain care and research and resulted in two reports outlining new directions for pain research , 4. The Established in 2018 when the U.S. Congress added $500 M to the NIH base appropriation, the NIH HEAL Initiative consulted a broad range of partners including other government agencies , as well as academic centers, the private sector, and community patient advocates, to identify needs and opportunities and to develop “an innovative, action-oriented research plan for HEAL,” focused on improving treatments for opioid misuse and addiction and for advancing strategies for pain management  are sets of required and optional CDEs with specific variables and their method of ascertainment across nine key pain-relevant domains . The HEAAddressing pain while reducing the risk of addiction requires a broad, action-oriented, multifaceted approach predicated on understanding pain biology and pathophysiology and leading to science-informed new treatments. The ultimate goal of these programs is to improve the efficiency and effectiveness of clinical trials toward enabling personalized, precise care.Preclinical and translational pain therapeutic development programs within HEAL start with target and asset discovery and validation, extend through into clinical trials, and encompass all clinical trial phases, including effectiveness research and pragmatic trials. Various pain management strategies are being tested including complementary and integrative approaches  and pain self-management approaches, as well as drugs and devices. HEAL preclinical research programs provide an avenue for focused study of pain mechanisms and therapeutics. These include preclinical testing platforms, animal models, human cell-based screening, tissue chips, and advanced imaging tools. HEAL studies incorporate techniques including neuroimaging, -omics, sensory testing, and psychosocial assessments to develop algorithms that will help predict the transition from acute to chronic pain and enable biomarker discovery, validation, and implementation.HEAL pain programs are shown in in vitro assays to screen for absence of opioid activity and abuse liability as well as for off-target and neurological side effects, followed by an evaluation in in vivo pain models.HEAL pain translational research programs provide the link connecting new target and therapeutic discovery and development to clinical trials. The Preclinical Screening Platform for Pain provides an evaluation of potential therapeutic assets in a tiered series of Within HEAL clinical pain programs, the HEAL Discovery and Validation of Biomarkers, Endpoints, and Signatures program seeks to identify and validate biomarkers, endpoints, and signatures of various pain conditions. This program aims to deepen the understanding of cohort- and individual-level variations in pain perception, chronification, and response to treatment. The Back Pain Consortium Research Program (BACPAC) is studying a digital health platform that integrates quantitative spinal motion metrics, patient-reported outcomes, and consideration of patient preferences for treating low back pain. BACPAC has built a translational, patient-centered model to inform effective and personalized therapies for chronic low back pain.Moving into clinical testing, the Early Phase Pain Investigation Clinical Network (EPPIC-Net) seeks novel or repurposed pain therapeutics from academic researchers and pharmaceutical companies. For accepted assets, EPPIC-Net designs and conducts phase 2 clinical trials and can test proposed biomarkers in its network that joins expert pain researchers and research centers. Applicants to this program collaborate in clinical trial development and, importantly, retain intellectual property rights to their asset. EPPIC-Net explores novel study designs, recently establishing a platform protocol providing efficient and robust testing of novel therapeutics for diabetic peripheral neuropathy. The Pragmatic and Implementation Studies for the Management of Pain to Reduce Opioid Prescribing program integrates evidence-based interventions into healthcare systems with pragmatic clinical trials and implementation science embedded in real-world settings.To date, $3.2 billion has been invested in HEAL research, with more than 1,800 projects funded since its inception in 2018. HEAL has made substantial progress in this short time.•The Tailored Non-Pharmacotherapy Services for Chronic Pain: Testing Scalable and Pragmatic Approaches (RESOLVE) pragmatic trial compares the efficacy of two telehealth approaches to cognitive behavioral therapy for chronic pain. Establishing the utility of remote health approaches is particularly important to enable accessibility and inclusion of rural participants and of populations with limited ability to travel for in-person care.•KnowPain: HEAL investigators have piloted a wrist-worn monitoring device collecting robust physiologic and kinematic measurements. In people living with chronic low back pain, they have shown that 7-day sensor data correlated strongly with self-reported outcomes of patient pain and function. SPRINT (Signature for Pain Recovery In Teens): The SPRINT program collects robust multimodality data from teens with chronic musculoskeletal pain, utilizing techniques that include brain imaging, motor and sensory evaluations, psychological functional assessments, and genetic and molecular profiling. Big data and machine learning algorithms will be developed and used to identify the biomarkers of pain persistence and pain resilience in this underserved population.•Development and use of decision-making tools embedded into electronic health record systems. Offering various treatment options can help patients manage their own pain by selecting non-drug pain care after surgery, as well as help clinicians support that choice.•The Hemodialysis Opioid Prescription Effort (HOPE) research study is testing various non-opioid treatment approaches in dialysis patients. This research is testing the use of a virtual pain coach during dialysis as well as administering buprenorphine for pain relief.•Virtual reality allows patients with low back pain to experience 3D immersive environments, such as walking up a waterfall or exploring a virtual city.•Discovery of a biomarker signature for neuropathic pain: This project has identified sub-basal corneal microneuromas in patients with neuropathic corneal pain, differentiating it from dry eye disease. Research to validate this potential biomarker is ongoing.•Development of a living pain circuit : a tissu•Non-invasive brain stimulation that combines independently controlled electromagnetic and ultrasonic fields provided pain and functional relief in a small study of patients experiencing pain due to carpal tunnel syndrome.HEAL-funded studies have advanced several promising pain therapeutic candidates to investigational new drug and investigational device exemption filings with the Food and Drug Administration. HEAL investigators have patented novel targets for chronic pain, inflammatory and visceral pain, and migraine. Selected examples appear below.HEAL pain research aims to improve the quality of life and reduce pain by developing and implementing safe and effective strategies for pain prevention and treatment that alleviate risks of opioids. This multifaceted research investment spans the investigational spectrum: from target discovery and validation to translational research to clinical trials and comparative effectiveness studies—in addition to growing and sustaining a vibrant pain research workforce. HEAL research is leading the way to precision medicine for the millions of Americans who live with pain. New or improved pharmacologic, non-pharmacologic, and integrated models of pain management are being tested and refined toward assembling a broad array of safe and effective approaches predicated on the needs of those with lived pain experience and their caregivers.


Following health system integration of an academic medical center and 10 community hospitals, efforts were made to unify the individual antimicrobial stewardship programs (ASP) and standardize resources within a system-wide Antimicrobial and Diagnostic Stewardship Program (NM ADSP). We assessed the impact of optimizing our public-facing website with updated resources, improving platform usability and convenience, and promoting the new ADSP website to stakeholders.Previously conducted focus group sessions of the general public and internal questionnaires to clinicians were used to assess the value of antimicrobial stewardship (AS) and available resources/education. Our system ADSP team worked to assess and merge existing AS resources across each site. Concurrently, the ADSP team partnered with marketing specialists and digital content creators at our institution to produce and launch the new ADSP website. Tracking of total website pageviews per week for 3 months before and 3 months after the ADSP website optimization was evaluated.p < 0.001).Feedback from focus groups and clinical users confirmed the value of a website as a convenient and accessible platform in disseminating important AS resources and education to a broad audience. From these assessments, we identified and prioritized high-use AS resources and education content across the system  and prioritized these on the home page. Other information identified as useful included site-specific practice guidance, about us, clinical & patient education, news/events, and residency/fellowship information, which were also posted on the home page. A significant difference in the median unique website views per week was observed after optimization and launch of the new ADSP website (pre: 347; post: 524, NM ADSP Website ResourcesAntimicrobial stewardship is a collective effort. Establishing an organized and resourceful AS public-facing website that is user-friendly and reliable for our stakeholders betters our chances of improving the use of anti-infectives and reducing the threat of antimicrobial resistance. Our experience may be useful to identify educational best practices for enhanced ASP impact at other institutions.All Authors: No reported disclosures


Based on the social network theory, this study utilizes knowledge absorption capacity as the mediating variable and technology turbulence as the moderating variable; furthermore, it focuses on China’s intelligent manufacturing industry data to explore the effect of the intelligent manufacturing enterprise innovation network on technology innovation performance and the regulating mechanism of technology turbulence. Based on the patent data obtained from Derwent Database (survey period: 2016–2020), the empirical analysis indicates the following: (1) Network relationship, network location, and network density are significantly and positively correlated with technology innovation performance; however, network size exerts no significant effect on technology innovation performance. (2) Network relationship strength, network location, and network density exert significantly positive effects on the two dimensions of knowledge absorption capacity, namely the In-degree and the Out-degree. Network size exerts no significant effect on knowledge absorption capacity. (3) Knowledge absorption capacity exerts a partial mediating effect on the relationship between innovation network and technology innovation performance. (4) The three dimensions of innovation network that exert a significant effect on technology innovation performance are positively correlated with the interaction terms of technology turbulence, which indicates that the interaction terms, namely innovation network and technology turbulence, exert a positive impact on technology innovation performance through knowledge absorption capacity, and that the moderating effect of technology turbulence exerts a role through knowledge absorption capacity. Finally, this study postulates implementations and policy proposals for enhancing the innovation performance of intelligent manufacturing enterprises. Intelligent manufacturing, the focus of the deep integration of information technology and industrialization, exerts a positive role in promoting China’s development towards an manufacturing power. The "Made in China 2025" proposal has exceedingly promoted the development of intelligent manufacturing in China. Currently, product diversity and knowledge diversity, proliferation, and integration are crucial for realizing intelligent manufacturing . The devChinese manufacturers can quickly acquire domain expertise through the application of intelligent manufacturing technology, and the turbulence in the transformation stage may offer a valuable opportunity for leapfrog development. Therefore, exploring the influencing factors pertaining to the development of intelligent manufacturing innovation technology is conducive to addressing development bottlenecks and effecting timely measures . ScholarBased on the preceding literature analysis, scholars mainly analyze innovation characteristics from three dimensions, namely connection strength, network density, and network size. In addition, the social network theory and the knowledge-based theory indicate that a crucial feature of innovation networks is knowledge flow  . TherefoBased on the previous analysis, innovation networks and knowledge absorption capabilities crucially affect the technology development of the intelligent manufacturing industry; however, there is a lack of research in this field. In addition, technological turbulence refers to the uncertainty, complexity, and unpredictability of technological changes. The turbulent technological environment introduces a certain degree of difficulty, which limits enterprise innovation and presents new challenges ; moreoveThe innovation network was first defined by Freeman as a basic institutional system for addressing systemic innovation, which is primarily connected through innovation cooperation between organizations . SubsequNetwork relationship refers to the process through which an organization forms partnerships with members of the network to obtain complementary resources  from the outside world. Rojas et al.  divided Hypothesis 1: The strength of the network relationship positively affects the technology innovation performance of enterprises.Network location is the ultimate result of establishing relationships between an organization and other members of the innovation network, reflecting the position of the enterprise in the network and the ability of the organization to absorb and diffuse new knowledge based on its embedded innovation network. The resources and technological knowledge obtained by the organization in the network are its internal driving force through which its own technology innovation performance can be enhanced . Based oHypothesis 2: Network centrality exerts a positive influence on the technology innovation performance of enterprises.Network structure has been defined from different perspectives . Based oNumerous scholars have analyzed the influence of network structure on organizational technology innovation performance from two variables, namely resources and capabilities . Based oHypothesis 3a: The network scale positively affects the technology innovation performance of enterprises.Hypothesis 3b: Network density positively affects the technology innovation performance of enterprises.In regard to the open environment of innovation networks, organizations obtain heterogeneous resources through establishing complementary cooperation with network members, and the acquisition of heterogeneous knowledge is closely related to the organization’s knowledge absorption capacity . KnowledSpecifically, the above research results indicate that strong network relationships can enable organizations to acquire more valuable new knowledge and resources , and theHypothesis 4: The network relationship strength positively affects knowledge absorption ability.Hypothesis 5: The network location centrality positively affects knowledge absorption ability.Hypothesis 6a: Network size positively affects knowledge absorption capacity.Hypothesis 6b: Network density positively affects knowledge absorption ability.It is generally believed that the identification, acquisition, and application of external knowledge are positively correlated with organizational performance , and theHypothesis 7: Knowledge absorption ability exerts a mediating role between innovation networks and technology innovation performance.Technology turbulence refers to the scenario in which industrial technologies exhibit uncertain changes , which wH8a: Technology turbulence positively moderates the influence of network relations on technology innovation performance through knowledge absorption capacity.H8b: Technology turbulence positively moderates the influence of network location on technology innovation performance through the knowledge absorption capacity.H8c: Technology turbulence positively moderates the influence of network size on technology innovation performance through the knowledge absorption capacity.H8d: Technology turbulence positively moderates the influence of network density on technology innovation performance through the knowledge absorption capacity.Scholars indicate that patents are the characterization of technological innovation and the most powerful tool through which technological innovation can be measured. Numerous studies have analyzed knowledge activities among enterprises and organizations based on patent analysis . TherefoThis study utilizes Thomson Data Analyzer (TDA) social network analysis software to plot the patent cooperation network for each year, and, subsequently, utilizes UCINET software to calculate the network relationship strength, intermediate centrality, network size and network density, and node out-degree and in-degree of these patent reference networks; thus, the measurement indicators of these variables is obtained.Herein, the patent cooperation network was plotted by the Thomson Data Analyzer (TDA) social network analysis software, and the UCINET software was utilized to calculate the following measurement indicators: network relationship strength, intermediate centrality, network size and network density, and node out-degree and in-degree.(1) Dependent variablesBased on the literature review, this study selects enterprise technology innovation performance (PF) as the dependent variable. Because patent applications may fail, the utilization of application data alone cannot characterize the technology transformation output of a company. However, the Derwent Innovations Index (DII) contains approved patent data. Therefore, this study selects the patent data included in the DII of the company in year t to measure the company’s technology innovation performance.Independent variables(2) Based on the preceding literature analysis, this study divides innovation network into four dimensions, namely network relation (RS), network location (BC), network size (SC), and network density (DE), and utilizes them as independent variables; thus, their effects on dependent variables are respectively analyzed. The specific measurements of independent variables are as follows:Although questionnaires are widely utilized by contemporary scholars as the main tool for measuring network relations, knowledge flow in the innovation network is bidirectional, and the object of the questionnaire, which often fails to investigate partners simultaneously, is only sample enterprises . In addiIntermediate centrality is utilized to measure the strength of the network subject’s control over network resources, and represents the shortest path frequency of any pair of subjects connected through the subject . In the In the process of building innovation networks, isolated points often exist; enterprises that are not connected with any nodes should be proposed. Therefore, the network size (SC) refers to the number of node enterprises that can be connected with other members .Network density (DE) refers to the ratio of the actual connection frequency between network nodes to the number of possible connections in the network; thus, it represents the strength of the knowledge flow in the innovation network .(3) Intermediate variablesThe knowledge absorption capacity of an enterprise is defined as the ability of an organization to acquire, accept, transform, and output knowledge. The knowledge absorption process includes not only self-transformation but also knowledge spillover. Therefore, in-degree (ID) is utilized to measure the ability of knowledge transformation, and out-of-degree (OD) is utilized to measure the ability of an enterprise to export knowledge. In the patent citation networks, the line points to the node, which indicates that the node introduces the patent. Conversely, the lines sent by the node represents the patent output. Therefore, the in-degree can be obtained by calculating the frequency of the lines pointing to the node organization in the innovation network . The out-degree is obtained by calculating the number of connections to other members organized by nodes , 59.(4) Moderator variablesThe knowledge absorption capacity of an organization is often affected by the uncertainty of the technological environment. Therefore, according to , technol(5) Control variablesThis study introduces enterprise age, R&D investment, nature of property rights  and pateTo examine the impact of the dimensions of innovation networks on technology innovation performance, the study utilized a panel model that refers to the study conducted by Liang Y et al. , Qian X (1) Construction of a mediation model for knowledge absorption capacity.First, to examine the impact of enterprise innovation networks on enterprise technology innovation performance (PF), hypotheses 1, 2, 3a, and 3b are proposed; furthermore, the models constructed herein are as follows:Second, to test the impact of various dimensions of enterprise innovation network on knowledge absorption capacity, the following two models are constructed based on hypotheses 4, 5, 6a, and 6b.The third step entails testing the mediating effect of knowledge absorption capacity. Based on Hypothesis 7, the following three models are designed.In addition, for comparative analysis, this study tests the influence of knowledge absorption capacity on technology innovation performance (PF). Based on Hypothesis7, this study constructs the following two models.(2) The moderating effect of technology turbulenceTo test the moderating effect of technology turbulence on the relationship between innovation networks and enterprise technology innovation performance (PF) through the knowledge absorption capacity , this study refers to the testing program designed by Su and Li ; thus, HThe variables utilized in the preceding model and their respective calculation methods have been explained in a preceding section; this notwithstanding, i denotes the sample individual, and t denotes the year.First, the results pertaining to the descriptive statistical analysis of variables are depicted in Herein, mixed effects and fixed effects are selected using a likelihood ratio test (L.R test). If fixed effects are determined, random effects and fixed effects are selected by the Hausman test. The test results are illustrated at the bottom of Herein, multiple linear regression models 1 to 8 are constructed; thus, the aforementioned theoretical assumptions are verified . Model 5Models 1 and 2 indicate that network relationship strength (RS), network location  exert significantly positive effects on the two dimensions of knowledge absorption capacity. Therefore, the empirical results support Hypothesis4, Hypothesis 5, and Hypothesis 6b. Network size (SC) exerts no significant influence on knowledge absorption capacity; therefore, Hypothesis H6a fails the test. This conclusion verifies the aforementioned theoretical derivation, and the knowledge flow of innovation network exerts a positive role in promoting technological innovation .2 in Model 6 and Model 7 are greater than that in models 1 and 2, which also verifies the rationality of the mediating effect. The network size (SC) does not exert a significant impact on knowledge complementarity and technology innovation performance (PF) due to the frequent interaction and increased awareness of cooperation among participants, as well as the reduction of isolated enterprises.Models 3 and 4 indicate that the two dimensions of knowledge absorption capacity, namely the In-degree (ID) and the Out-degree (OD), respectively, exert a significantly positive impact on technology innovation performance (PF). Models 6 and 7 indicate that knowledge absorption ability exerts a significant mediating effect on the impact of the innovation network  on technology innovation performance (PF); thus, the results support hypothesis 7. The values of RModel 8 comprehensively demonstrates the relationship between innovation network, knowledge absorption capacity, and technology innovation performance. The results indicate that after the introduction of the two dimensions of knowledge absorption capacity, the correlation coefficient of the innovation network’s influence on technology innovation performance decreases significantly, which further verifies the intermediary effect. It can be observed that the network relationship (RS) exerts the greatest influence on technology innovation performance (correlation coefficient is 0.303**), and the network density (DE) exerts the least influence (correlation coefficient is 0.211*), whereas the network size (SC) exerts no significant influence on technology innovation performance (PF).To verify hypothesis H8, the technology turbulence (UT) of the regulating variable should be tested, and, subsequently, the knowledge absorption capacity of the intermediate variable should also be tested. The results are depicted in 2 demonstrates the rationality of the final model (Model 12).When conducting a statistical regression model, this study adopted a gradual addition of variables. Thus, it compared and analyzed the impact of independent variables on technological innovation performance; the impact of independent variables and intermediary variables on technological innovation performance; and the impact of independent variables, intermediary variables, and moderating variables on technological innovation performance, simultaneously. Therefore, the impact of variable introduction on empirical analysis results can be effectively analyzed. Comparing Tables If we consider the intelligent manufacturing industry, this study explores the impact pertaining to various dimensions  of innovation networks (patent citation networks) on technology innovation performance (PF). Based on the social network and knowledge creation theories, the study reveals the impact exerted by the various dimensions of innovation networks on knowledge absorption capacity. Based on the preceding analysis, this study utilizes knowledge absorption capacity as the intermediate path; thus, it analyzes the impact mechanism of innovation networks on the technology innovation performance of intelligent manufacturing enterprises. The main conclusions of this study are as follows:(1) With the exception of the network size, the dimensions associated with the innovation network of intelligent manufacturing enterprises exert a significantly positive impact on technology innovation performance. With regard to the influence on technology innovation performance, the dimensions are ranked as network relationship strength, network location, and network density, in decreasing order; moreover, network size exerts no significant influence on innovation performance. The network relationship in the innovation network of the intelligent manufacturing industry is reflected as the process pertaining to the complementary learning of node enterprises; the network location is reflected as the process through which node enterprises utilize more opportunities to acquire new knowledge; and the network density is reflected as the intensity of knowledge flow in the innovation network. Specifically, node enterprises in the innovation network acquire, integrate, transform, and create new knowledge through complementary cooperation and learning, and deepen and utilize the new knowledge within the organization , 74. In (2) The intelligent manufacturing innovation network  exerts a significantly positive influence on knowledge absorption capacity. Under the innovation network environment, the open innovation activities of node organizations enable organizations to continuously acquire heterogeneous knowledge, which can enhance the value of the organizations’ existing resources, enhance resource diversity, increase the amount of knowledge possessed by organizations, immensely promote the absorption and transformation of more diverse knowledge by organizations, and enhance the knowledge absorption capacity of organizations . In addi(3) Knowledge absorption capacity exerts a partial mediating role in the relationship between the innovation network and technology innovation performance (PF) of intelligent manufacturing enterprises, in which the influence of In-degree (ID) is greater than that of Out-degree (OD). Knowledge absorption capacity refers to the ability of an organization to acquire, integrate, and transform heterogeneous resources continuously and dynamically . Node orThe practical significance of this study can be explained as follows: although innovation networks exert a promoting effect on enterprise innovation performance and have been widely recognized by scholars, the conclusions obtained from this study provide further guidance for the specific strategies that enterprises should adopt when constructing inter organizational collaborative innovation networks. Based on the aforementioned conclusions, this study offers the following proposals:(1) The heterogeneity of knowledge in innovation networks promotes cooperation between enterprises and other innovation entities, strengthening the density and intensity of cooperation. As the main source of innovation output, enterprises crucially facilitate innovation activities . Intelli(2) Intelligent manufacturing enterprises should consider the enhancement of knowledge absorption capacity as the core path of the innovation network and technology innovation performance transformation, and the top management should crucially focus on the construction and enhancement of organizational knowledge absorption capacity. Specifically, to maintain competitive advantages, intelligent manufacturing enterprises should build scientific strategic development plans, and the leadership should deeply understand the effect of knowledge absorption capacity on long-term organizational development. In daily work plans, they should strengthen the organizational learning ability, actively perform organizational learning activities, and enhance the ability of members to acquire new knowledge. Actively quoting new technical talents is also a crucial method of promoting innovation diversity.(3) The government should deeply recognize the cluster innovation effect of the intelligent manufacturing industry. The significant influence of network density on technology innovation performance reveals the positive driving force of cluster development on industrial innovation. By utilizing the timely promulgation of relevant policies to promote the development of an intelligent manufacturing cluster, the innovation activities of intelligent manufacturing enterprises are effectively promoted. While encouraging investment in industrial R&D and innovation, the government should clarify the knowledge requirements and differences in innovation capabilities of innovation entities within the industry, comprehensively leverage the innovation driven advantages occasioned by the dynamic nature of innovation network knowledge, and formulate rational policies and systems to actively perform macroeconomic regulation.This study presents three theoretical contributions. (1) Currently, research on the impact of innovation networks on technological innovation is mainly limited to a certain characteristic attribute of the network, such as analyzing its impact on organizational innovation from the following perspectives: relationship embedding, network location, and knowledge heterogeneity –20. ThisThis study exhibits the following shortcomings. First, although it utilizes the most authoritative patent data for empirical analysis, the lag of the patent database also poses certain research obstacles. In addition, some advanced technologies, even confidential technologies, often do not apply for public patents; therefore, patent data exhibits certain limitations. Second, the study represents the innovation performance of a company based on the number of applied invention patents. The innovation performance of a company includes many aspects. Future research can further analyze the deep-seated factors of the company’s technological development from perspectives such as the number of novel products developed by the company and the nature of patents. Furthermore, there are many social factors that affect the development of technological innovation . Therefore, how to systematically and comprehensively position the trajectory and internal development mechanism of industrial technological innovation development is also a potential research direction. Finally, this study analyzed only the basic cooperative relationships among network members; however, different types of cooperative relationships exist. Future research can refine the types of cooperation into categories such as industry university research cooperation, state-owned and non-state-owned enterprise cooperation, and Sino–Foreign enterprise cooperation and further analyze the cooperative relationships between network node organizations; thus, the impact that the nature of cooperative relationships exerts on innovation performance and policies can be analyzed.S1 Data(RAR)Click here for additional data file.


Gynostemma pentaphyllum were found to possess a protective effect in liver diseases. Here, we obtained a naturally abundant gypenoside, XLVI, and evaluated its liver protection activity in both animal and cellular models. The results showed that it ameliorated acute and chronic liver injuries and lightened the process of fibrogenesis in vivo. XLVI can inhibit TGF-β-induced activation of hepatic stellate cells and ECM deposition in vitro. The underlying mechanism study verified that it upregulated the protein expression of protein phosphatase 2C alpha and strengthened the vitality of the phosphatase together with a PP2Cα agonist gypenoside NPLC0393. These results shed new light on the molecular mechanisms and the potential therapeutic function of the traditional herb Gynostemma pentaphyllum in the treatment of liver fibrosis. Liver fibrosis resulting from chronic liver damage is becoming one of the major threats to health worldwide. Active saponin constituents isolated from  Liver fibrosis occurs in chronic liver injury, such as that caused by cholestasis, alcohol abuse, viral infection, drug abuse, and metabolic and autoimmune disorders, and may further lead to cirrhosis with portal hypertension, liver failure, and even liver carcinoma . Liver fGynostemma pentaphyllum (Thunb.) Makino, also named Jiaogulan in Chinese, has been traditionally used as a medicinal herb in Eastern Asia for a long time. The crude extracts from Gynostemma pentaphyllum have multiple pharmacological effects, including hepatoprotective, anti-hyperlipidemia, and anti-inflammatory activities, but show no clear toxicity to animals . Procedures and protocols were performed in strict accordance with The Care and Use of Laboratory Animals, published by The United States National Institutes of Health .


This study focuses on New World Vultures, a group of seven scavenger bird species with ecological significance. Despite their importance, there is limited knowledge about their evolutionary history and conservation needs. Recent advances in understanding their evolutionary relationships have paved the way for addressing these gaps using phylogenetic methods. By analyzing the species’ ancestral distribution in the Americas, we employed two techniques to identify historical dispersion patterns. This study pinpointed South America as their original area, with subsequent recolonization of North America by certain species. To guide conservation efforts, we used two indices. The Evolutionary Distinctiveness (ED) index measured species’ uniqueness according to their phylogeny, while the Global Endangerment (GE) index mapped phylogenetic diversity. The findings highlighted the Black Vulture, California Condor and Andean Condor as priority species based on their uniqueness and evolutionary significance. Additionally, we identified crucial regions for conservation, including the lowlands of the Amazon River basin, the Orinoco basin and various areas along the Guiana Shield’s tributaries. This research underscores the importance of combining evolutionary and ecological insights and tools to fill knowledge gaps about species of concern. By doing so, we can formulate effective strategies to protect these species in the face of ongoing biodiversity loss.Coragyps atratus, Gymnogyps californianus and Cathartes aura. We identified the Black Vulture, G. californianus and Vultur gryphus as priority species based on ED and “Evolutionary Distinct Globally Endangered” (EDGE) indexes, and the lowlands of Amazon River basin and the Orinoco basin and some tributaries areas of the Guiana Shield were identified as the priority areas when mapping the phylogenetic diversity. This study highlights the importance of filling knowledge gaps of species of conservation concern through the integration of evolutionary and ecological information and tools and, thus, developing adequate strategies to enhance the preservation of these species in the face of the current loss of biodiversity.The New World Vultures (Cathartidae) include seven species of obligate scavengers that, despite their ecological relevance, present critical information gaps around their evolutionary history and conservation. Insights into their phylogenetic relationships in recent years has enabled the addressing of such information gaps through approaches based on phylogeny. We reconstructed the ancestral area in America of the current species using two regionalization schemes and methods: Biogeography with Bayesian Evolutionary Analysis (BioGeoBears) and Bayesian Binary Model–Monte Carlo Markov Chains (BBM–MCMC). Then, we identified the priority species and areas for conservation by means of the Evolutionary Distinctiveness index (ED), as a proxy of the uniqueness of species according to phylogeny, and the Global Endangerment index (GE), mapping phylogenetic diversity. We found that the ancestral area of New World Vultures in America corresponds to South America, with dispersal processes that led to a recolonization of North America by  Vulture gryphus), Black Vulture (Coragyps atratus), California Condor , Greater yellow-headed Vulture (Cathartes melambrotus), King Vulture (Sarcoramphus papa), Lesser yellow-headed Vulture (Cathartes burrovianus) and Turkey Vulture (Cathartes aura) [The New World Vultures (Family: Cathartidae) comprise an emblematic group of raptors that includes seven species of obligate scavenging birds: the Andean Condor (es aura) ,2,3.Although this family has an undisputed monophyletic status, historically, the phylogenetic position of New World Vultures in avian phylogeny varies among different studies ,5,6,7,8.http://datazone.birdlife.org/species/search accessed on 10 October 2023). There, the Lesser yellow-headed Vulture is distributed from western Mexico to northern Argentina in areas associated with water bodies, secondary forests and forest edges [Currently, the New World Vultures are restricted to the Americas and reach their highest diversity in the Neotropical region . Among these measures, the evolutionary distinctiveness (ED) captures the evolutionary uniqueness of the species, shedding light on more detailed aspects of phylogenetic diversity. Also, when the ED is weighted with the extinction risk, this provides an index known as EDGE, which becomes a useful variable tool in identifying and prioritizing irreplaceable key species in clades and ecosystems [Thanks to the most recent contributions to the reconstruction of the tree of life in the last two decades  to infer the most likely ancestral area of the most common recent ancestor (MCRA) of extant species of New World Vultures; and (ii) to estimate the phylogenetic diversity, evolutionary distinctiveness and EDGE values for this group of birds.We used the most complete and robust molecular phylogeny of the New World Vultures inferred by Johnson et al.  for all https://github.com/FePhyFoFum/phyx accessed on 10 October 2023) in combination with the MCC. For the inference of the MRCA of the New World Vultures, we performed biogeographic reconstructions by setting two large-scale regionalization schemes: a first biogeographic reconstruction in which we used the Neotropical and Nearctic regions and a second biogeographic reconstruction in which we used three more specific areas, namely (i) North America (including the United States and northern Mexico), (ii) Central America  and (iii) South America. We did not increase the spatial resolution of the analyses to include more areas, since the probabilities of the ancestral areas calculated by the algorithm (<15%) were very low relative to the uncertainty (20%).We used a sample of 151 trees by Johnson et al.  sourced BioGeoBears) and Bayesian Binary Model–Monte Carlo Markov Chains (BBM–MCMC) [BioGeoBears is an R package incorporated in RASP that allows one to infer ancestral areas by probabilistically comparing several models, namely Dispersal–Extinction–Cladogenesis (DEC), a likelihood interpretation of Statistical Dispersal–Vicariance Analysis (DIVALIKE), a likelihood interpretation of the Bayesian inference of historical biogeography for many discrete areas method (BAYAREALIKE) and a version of each of these models including the “J” parameter [We tested two methods implemented in Reconstruct Ancestral State in Phylogenies (RASP): Biogeography with Bayesian Evolutionary Analysis (BM–MCMC) . BioGeoBarameter . We comparameter . In thisarameter ,51. In Bevol.distinc function implemented in the picante R package [edge.species (S1).The identification of EDGE species requires the analysis of two components: Evolutionary Distinctiveness (ED) and Globally Endangered (GE) scores, based on the IUCN Red List categories. To this end, firstly, we calculated the Evolutionary Distinctiveness (ED) by “Fair proportion” of each species using the  package . The “Fa package . Then, t package  into num package  as follo package : EDGE = pd function in the picante R package [phyloregion R package [polys2comm function with a resolution of 1 × 1 degree grid cells. Then, we calculated the phylogenetic diversity with the pd function and, finally, we projected the results onto a map of America using the plot_swatch function. In both analyses, phylogenetic diversity was calculated as the total length of all branches of a set of taxa in a phylogenetic tree [In order to quantify the loss of the phylogenetic diversity of New World Vultures, we tested for hypothetical scenarios of extinction of species that reached the highest ED and EDGE values. First, we calculated the phylogenetic diversity on the phylogeny of the whole clade with the  package . This fu package  and the  package . We convtic tree .BioGeoBears model that best fits the data in both regionalization schemes is DEC  score for New World Vulture species was 8.83 Ma, with the Black Vulture (ED—12.32 Ma) and the Andean Condor (ED—10.90 Ma) reaching the highest values A. LinkinMultiple hypotheses about the center of origin of the New World Vultures have arisen. On the one hand, a North American origin was proposed  based onCoragyps dated from Late Oligocene/Early Miocene [Gymnogyps reached a wide distribution, even outside North America, during the Pleistocene [Cathartes radiated during the Pliocene in South America, and then a process of expansion of the distribution of the Turkey Vulture could have allowed this species to reach North America.Our results suggest that the radiation of the seven current species of New World Vultures took place in South America A,B. This Miocene ,60 that  Miocene . Then, t Miocene , a perio Miocene  and refeistocene . Regardiistocene . AlthougIt has been suggested that the radiation of megafauna in South America after the Middle Miocene and the consequent increase in carrion availability ,66 are rOur findings indicate that the Black Vulture, Andean Condor and California Condor must be considered conservation-priority species based on their uniqueness and evolutionary significance A. The BlDue to anthropogenic threats such as habitat degradation, poisoning with pesticides, lead intoxication, illegal capture, free-ranging dogs and shooting ,82,83,84We emphasize the Amazon basin as a key area for the protection of ~70% of the phylogenetic diversity of New World Vultures B. The AmIn this study, we underscore the critical significance of harnessing available resources to employ a diverse array of analytical phylogenetic methods. These approaches serve as powerful tools not only for bridging information gaps but also for advancing our understanding not just of the evolutionary trajectories of organisms but also of their conservation and management strategies. It is essential, however, to acknowledge and address certain inherent limitations within this study. One such limitation stems from the use of a phylogeny constructed based on a restricted set of genes. Additionally, the exclusion of closely related extinct taxa from our phylogeny is, regrettably, a consequence of the limited availability of suitable information. These limitations, namely the reliance on a gene-limited phylogeny and the omission of extinct taxa due to data constraints, inevitably constrain the resolution of our analytical approaches and, consequently, the depth of our inferences.In conclusion, our research not only highlights the invaluable role of comprehensive phylogenetic investigations but also underscores the need for continued efforts to address these limitations. For groups of species that have received minimal scientific attention, we advocate for dedicated research endeavors aimed at reconstructing dated molecular phylogenies that encompass all relevant species. By doing so, we can potentially illuminate previously uncharted facets of their biology, offering invaluable insights derived from a more comprehensive understanding of their evolutionary relationships.