Industrial structure upgrading is an important prerequisite for achieving regional ecological environment protection and high-quality development, and environmental regulation can improve the capacity of scientific and technological innovation and promote industrial structure transformation and upgrading. Based on the panel data of 78 cities in the Yellow River Basin, the relationships among environmental regulation, scientific and technological innovation, and industrial structure upgrading in the Yellow River Basin were analyzed using the mediating effect model and the panel threshold model. The results showed the following findings: (1) Although both formal and informal environmental regulations can promote industrial structure upgrading in the Yellow River Basin, regional heterogeneity and temporal stage characteristics are observed. (2) Transmission mechanism test results show that formal and informal environmental regulations directly affect industrial structure upgrading and indirectly act on it through the level of scientific and technological innovation, showing a significant mediating effect. (3) Taking scientific and technological innovation as the threshold variable, formal environmental regulations have a corresponding relationship with industrial structure upgrading in the form of a broken line, and informal environmental regulations significantly promote industrial structure upgrading after scientific and technological innovation crosses a certain threshold. Finally, we discuss the article and make corresponding suggestions in terms of environmental regulation and technological innovation. As an important ecological defense, economic zone, and energy resource base in China, the Yellow River Basin holds a crucial position in China’s economic and social development and ecological security . The YelEnvironmental regulation mainly refers to the government’s institutional arrangement to constrain the pollutant discharge behavior of economic entities by promulgating administrative systems, activating market mechanisms, and exercising the role of the public. It aims to address the failure of the market in environmental externalities, intervene in the economic activities of various relevant economic entities, and seek harmonious development of the social economy and the ecological environment ,11,12. ASome studies focused on the direct impact of environmental regulations on industrial structure upgrading. Early studies generally supported the compliance cost theory, which argued that while increasing social welfare, environmental protection necessarily increases the production costs for manufacturers, thus limiting their economic activities and ultimately discouraging industrial structure upgrading . For exaSome other studies focus on the indirect impact of environmental regulations on industrial structure upgrading. Environmental regulations can indirectly impact industrial structure upgrading through multiple paths. Zhang et al. explored the effect of environmental technology standards on enterprise green transformation and the action mechanism using data from the Chinese manufacturing industry from 2000 to 2006, and the results showed that environmental technology standards indirectly contribute to the green transformation of the manufacturing industry through three technological modification mechanisms: terminal governance, capital renewal, and resource restructuring . Hu and In summary, the existing literature provides some basis for this study but is not free from limitations. First, most of the existing studies are based on national, provincial, or city levels. The ecological protection and high-quality development of the Yellow River Basin have been established as a major strategy for China’s national and regional economic development. Thus, the existing studies lack an examination of the Yellow River Basin. Second, existing studies mostly examine the impact of formal environmental regulations on industrial structure upgrading, thus ignoring the different impacts of informal environmental regulations on industrial structure upgrading. Finally, although some scholars have examined the relationships among environmental regulations, scientific and technological innovation, and industrial structure upgrading, empirical studies integrating formal and informal environmental regulations, technological innovation, and industrial structure upgrading into the same framework are scarce. Based on the above, this study extends the existing research in the following aspects; First, this paper takes 78 cities in 9 provinces/autonomous regions along the Yellow River Basin as the study area to theoretically analyze and empirically test the relationships among environmental regulations, technological innovation, and industrial structure upgrading. Second, the relationships among environmental regulations, technological innovation, and industrial structure upgrading are examined from the perspective of formal and informal environmental regulations. Finally, this study introduces a mediating effect model and a panel threshold model to investigate the mediating effect of technological innovation between environmental regulations and industrial structure upgrading and examine whether environmental regulations have a nonlinear relationship with industrial structure upgrading under different levels of scientific and technological innovation. This study could provide reference and guidance for exploring the effective path by which environmental regulations and scientific and technological innovation synergistically promote industrial structure transformation and upgrading.The rest of the paper is organized as follows: The direct impact of formal environmental regulations on industrial structure upgrading is as follows: On the one hand, formal environmental regulations promote industrial structure transformation and upgrading through the industrial transfer effect. According to the pollution haven hypothesis, pollution-intensive enterprises often move from countries (regions) with relatively strict environmental regulations to countries (regions) with relatively lax environmental regulations to avoid the compliance costs associated with environmental regulations, thus advancing the industrial structure of their countries (regions) from a lower to a higher stage ,33,34. OThe direct impact of informal environmental regulations on industrial structure upgrading is as follows: On the one hand, with increased concern about environmental issues and increased demands for environmental quality due to the promotion of ecological civilization construction, the public often forces pollution-intensive enterprises to reduce environmental pollution and undertake green technological innovation through negotiation and media exposure, thus promoting the clean development of pollution-intensive industries ,38,39. OHypothesis  1:both formal and informal environmental regulations promote industrial structure upgrading in the Yellow River Basin, and the effect of informal environmental regulations on industrial structure upgrading is stronger than that of formal environmental regulations.Formal environmental regulations influence industrial structure upgrading through technological innovation. Based on the Porter hypothesis, the effects of appropriate environmental regulations include stimulating enterprise innovation, increasing innovation capital investment, acquiring advanced technologies, and conducting scientific and technological innovation activities, thus producing the innovation compensation effect and advancing the enterprises toward clean development and high-value-added products ,45,46. IInformal environmental regulations influence industrial structure upgrading through technological innovation. First, the gradually extensive disclosure of environmental information and the increasingly stringent public scrutiny force enterprises to increase their investment in technological innovation, reform their production technology, and improve their raw material utilization out of concern for damage to their reputation and the increased risk of publicized pollution incidents, thus promoting industrial structure optimization and adjustment ,55,56. SHypothesis  2:formal and informal environmental regulations indirectly contribute to the industrial structure upgrading in the Yellow River Basin through the mediator variable of scientific and technological innovation.To test the direct effect of environmental regulations on the industrial structure upgrading in the Yellow River Basin, the following benchmark regression model is constructed:itStur denotes the industrial structure upgrading of city i in year t; iter denotes environmental regulations, which are decomposed into formal environmental regulation (Fer) and informal environmental regulation (Ier); α0 is the intercept term; α1 and α2 are the regression coefficients of lner and lnX, respectively; iμ is the individual effect; itε is the stochastic perturbation term; and X is the control variable.In Equation (1), itTech denotes the level of scientific and technological innovation in city i in year t. The other variables are as described above. Equation (2) tests the impact of formal and informal environmental regulations on scientific and technological innovation, and Equation (3) tests the impact of formal and informal environmental regulations and scientific and technological innovation on industrial structure upgrading. If γ1 and ρ2 in Equations (2) and (3) are significant at the same time, then scientific and technological innovation is a mediator variable; if ρ1 in Equation (3) is not significant, then scientific and technological innovation is a full mediator variable.After the theoretical analysis and the proposal of research hypotheses, the following mediating effect model is constructed to test the mediating role of scientific and technological innovation:The panel threshold model is adopted to further analyze the path by which scientific and technological innovation, the mediator variable, affects the effects of formal and informal environmental regulations on industrial structure upgrading in the Yellow River Basin. Specifically, scientific and technological innovation is used as a threshold variable to study its moderating role via which formal and informal environmental regulations affect industrial structure upgrading in the Yellow River Basin. Based on the panel threshold effects, the model is specified as follows:Stru). The value-added proportions of the tertiary and secondary industries in prefecture-level cities are used to measure the industrial structure upgrading in the Yellow River Basin. If such proportions are on the rise, the economy of the Yellow River Basin is advancing towards servitization, and the industrial structure is upgrading [Industrial structure upgrading  emission intensity calculated with the entropy weight method.Formal environmental regulations (Fer). It is particularly important to accurately measure or evaluate the level of environmental regulations in a region and thus select and implement appropriate environmental regulation tools . ScholarInformal environmental regulations (Ier). Based on a previous calculation method, the level of education, per capita income, and population density were selected to measure the informal environmental regulation intensity . GeneralScientific and technological innovation (Tech). Given the availability and continuity of data, the level of scientific and technological innovation for the year was measured by the logarithm of the total number of invention patents, utility model patents, and design patents in prefecture-level cities ,64.Industrial structure upgrading is the result of multiple factors, such as environmental regulation and scientific and technological innovation, and is closely associated with factors such as economic development, fixed asset investment, opening up, urbanization, and consumption structure ,66. TherThe Yellow River Basin includes nine provinces , of which Sichuan Province was included in the Yangtze River Economic Belt Development Strategy in September 2016 and became part of the Yangtze River Economic Belt. The four cities (leagues) in eastern Inner Mongolia have close economic and trade ties with Northeast China and have been included in the Northeast Regional Revitalization Plan. Therefore, this study focused on eight provinces (autonomous regions) in the Yellow River Basin, including Qinghai, Gansu, Ningxia, Inner Mongolia (except for its eastern part), Shanxi, Shaanxi, Henan, and Shandong. We calculated the environmental regulation intensity based on the per-unit industrial wastewater emission intensity, per-unit industrial SO2 emission intensity, and per-unit industrial fume (dust) emission intensity, and relevant pollutant data will not be counted after 2018. Due to the serious missing data of some cities, 78 cities in the eight provinces (autonomous regions) were finally selected for the study considering the completeness and accessibility of data. The study period was from 2004 to 2018. Additionally, according to the research needs, the eight provinces (autonomous regions) along the Yellow River Basin were divided into the upper reach region , the middle reach region , and the lower reach region (Shandong and Henan). The data used in the study are mainly from the China City Statistical Yearbook, China Statistical Yearbook on Environment, China National Intellectual Property Administration, EPS database, and statistical bulletins of national economic and social development of the relevant cities. The missing values of some indicators are completed through interpolation and other methods. The relevant descriptive statistics for each variable are shown in Based on the above benchmark regression model, the logarithms of the variables were used to ensure the smoothness of the panel data time series and reduce the effect of heteroscedasticity. To avoid problems such as multicollinearity and spurious regressions, the LLC and IPS unit root tests were conducted . AccordiThe benchmark regression results of environmental regulations on the industrial structure upgrading in cities of the Yellow River Basin are presented in The differences in resource endowments are large, and the economic development is uneven in the upper, middle, and lower reaches of the Yellow River Basin. In the meantime, the impact of environmental regulations on the industrial structure upgrading in different regions also varies. Therefore, the fixed effects model was used to explore the impact of environmental regulations on industrial structure upgrading in different regions. Models (3) and (5) show the effects of formal environmental regulations on the industrial structure upgrading in cities of the upper and middle reaches and cities of the lower reach, respectively. The results show that the regression coefficients of formal environmental regulations in cities of the upper and middle reaches and cities of the lower reach are 0.02 and 0.01, respectively, which pass the 5% and 10% significance tests. Therefore, formal environmental regulations can promote industrial structure upgrading in cities of the upper and middle reaches and cities of the lower reach. However, the effect of formal environmental regulations on industrial structure upgrading is stronger in cities of the upper and middle reaches than in cities of the lower reach. The main reason is that the Yellow River Basin, especially the upper and middle reaches, is an important base of energy, heavy, and chemical industries with great coal consumption, where industrial development has long relied on power, steel, coal chemistry, nonferrous metallurgy, and other resource-intensive industries, and the proportion of heavy industries is high. After long-term, large-scale, high-intensity energy extraction and industrialization, the resource and environmental constraints are tightening, the regional development is out of balance, and the resources are approaching depletion. Thus, the more stringent formal environmental regulations are more likely to promote industrial structure upgrading in cities of the upper and middle reaches than in cities of the lower reach. Models (4) and (6) show the effects of informal environmental regulations on the industrial structure upgrading in cities of the upper and middle reaches and cities of the lower reach, respectively. The results show that the regression coefficients of informal environmental regulations in cities of the upper and middle reaches and cities of the lower reach are 0.77 and 0.48, respectively, both passing the 1% significance level test, indicating that informal environmental regulations can promote the industrial structure upgrading in cities of the upper and middle reaches and cities of the lower reach.Since 2012, China has attached unprecedented attention to environmental issues and included ecological civilization in the Report to the 18th National Congress of the Communist Party of China. Meanwhile, considering the dynamic path-dependent effect of regional industrial structure adjustment, the 2004 to 2018 period is divided into two, namely, 2004 to 2012 and 2013 to 2018, to further analyze the period heterogeneity effect of environmental regulations on industrial structure upgrading. Models (7) and (9) show the effects of formal environmental regulations on the industrial structure upgrading in the 2004 to 2012 period and the 2013 to 2018 period, respectively. The results show that the effect of formal environmental regulations on industrial structure upgrading is weaker in the former time period than that in the latter time period, and the significance test is not passed. Since 2013, the Chinese government has formulated, promulgated, and revised a series of laws and regulations on environmental protection. As a result, the intensity of formal environmental regulations has been increasing, which has promoted sustainable economic and social development and industrial structure optimization in the Yellow River Basin. Models (8) and (10) show the effects of informal environmental regulations on the industrial structure upgrading in cities of the Yellow River Basin in the 2004 to 2012 period and the 2013 to 2018 period, respectively. The results show that the effect of informal environmental regulations on the industrial structure upgrading in the Yellow River Basin is significantly positive during the study period, indicating that the public demand for better environmental quality is becoming increasingly urgent as environmental pollution brings more and more negative impacts to life. In the meantime, the rapid development of media and network industries increased the number of nongovernmental environmental organizations and further released the power of nongovernmental environmental protection. As a result, the intensity of informal environmental regulations gradually increased, which promoted the industrial structure upgrading and the industrial structure transformation from pollution intensive to low carbon.As for the control variables, the coefficient of economic development is significantly positive, indicating that high-quality economic development and the improvement of public living standards can effectively promote the industrial structure upgrading in the Yellow River Basin. Economic development optimizes the allocation of production factors, such as capital, technology, and labor, and drives industrial structure upgrading. The regression coefficient of the effect of fixed asset investment on industrial structure upgrading is significantly negative, indicating that the increase in fixed asset investment is not conducive to industrial structure upgrading in the Yellow River Basin. The probable reason is that fixed asset investment in the Yellow River Basin is mainly in coal, metallurgy, building materials, infrastructure, iron and steel, nonferrous metals, and other resource-intensive industries. The development of these industries is often at the cost of high energy consumption and an overdraft on the ecological environment. Thus, the productivity utilization is low, the resource waste is high, and the pollution emissions are intensive, which is not conducive to industrial structure upgrading. The regression coefficient of the effect of the opening-up level on industrial structure upgrading is significantly positive, indicating that the increase in the level of opening up is conducive to optimizing the industrial structure of the Yellow River Basin. Increased levels of opening up attract high-quality foreign investment and bring advanced production technologies and management experiences, thus improving the production factor allocation efficiency and industrial structure optimization in the Yellow River Basin.The mediating effect of scientific and technological innovation between formal environmental regulations and industrial structure upgrading is examined in The threshold effect is tested. Using scientific and technological innovation as the threshold variable and Stata 15.0 as the statistical software, the threshold effect test results and the panel threshold effect regression analysis results are obtained by repeatedly sampling 1000 times using the bootstrap sampling method.p-values are 0.002 and 0.020, respectively, which pass the 1% and 5% confidence tests. The F-statistics of the triple-threshold effect is 17.67, and the corresponding bootstrap p-value is 0.786, which fails the significance test, indicating that the triple-threshold effect is not significant. Therefore, formal environmental regulations have a double-threshold effect. The single-threshold value is 6.9735, and the double-threshold value is 7.4483. The F-statistic of the single-threshold effect of Ier is 43.09, and the corresponding bootstrap p-value is 0.010, passing the 5% confidence test. The F-statistic of the double-threshold effect is 18.32, and the corresponding bootstrap p-value is 0.1906, which fails the significance test, indicating that the double-threshold effect is not significant. Therefore, informal environmental regulations have a single-threshold effect, and the single-threshold value is 7.4483.As shown in Then, the threshold effect between informal environmental regulations and industrial structure upgrading in the Yellow River Basin is analyzed. Using informal environmental regulations as the core explanatory variable, it has a single-threshold effect on industrial structure upgrading with a threshold value of 7.4483. When scientific and technological innovation is below 7.4483, the regression coefficient of the effect of informal environmental regulations on industrial structure upgrading is 0.46 and passes the 1% significance test, indicating that informal environmental regulations can promote regional industrial structure upgrading when the level of scientific and technological innovation is low. When scientific and technological innovation is above 7.4483, the regression coefficient of the effect of informal environmental regulations on industrial structure upgrading is 0.55 and passes the 1% significance test, indicating that the effect of informal environmental regulations on industrial structure upgrading in the Yellow River Basin is significantly enhanced with the increase in the scientific and technological innovation level. To meet the public’s consumption demand for green products and services, enterprises will increase their investment of capital and efforts in the research and development of green products. Thus, green technological innovation capabilities are enhanced, and the proportion of green industries in the overall national economy is increased, which forces the upgrading of the industrial structure.Based on the panel, our study found that both formal and informal environmental regulations could promote industrial structural upgrading, which was consistent with existing research findings ,70,71. IOur findings help to raise the awareness of policy makers to improve industrial structure upgrading, to improve the scientific accuracy and relevance of environmental regulation policies and technology innovation policies, and to alleviate industrial structure upgrading challenges and achieve low carbon development, as well as to strengthen the interaction between environmental regulation and technological innovation and leverage technological innovation. Both formal environmental regulation, mainly by the government, and informal environmental regulation, mainly by citizens and others, can force manufacturers to strengthen technological innovation and support the development of energy-saving and high-tech industries. Technological innovation is an effective transmission path for environmental regulations to be used for industrial structure upgrading, and the government should encourage and support enterprises to carry out technological R&D activities and promote the transformation of innovation results into actual productivity.While this study systematically analyzes the impact of environmental regulation and scientific technological innovation on industrial structure upgrading, some limitations remain to be addressed in the future. First, due to the limitations of data collection, this paper period selected is from 2004 to 2018. Therefore, future research will focus on collecting multiple measures through multisource data in order to establish a more multidimensional and complete evaluation system for the dynamic assessment of industrial structure upgrading in the Yellow River Basin over a long period of time. Second, the influence of spatial spillovers was not considered when selecting the model . As a puBased on the panel data of 78 cities along the Yellow River Basin from 2004 to 2018, a comprehensive investigation of the environmental regulations, scientific and technological innovation, and industrial structure upgrading in the Yellow River Basin was conducted using the panel fixed effects model, mediating effect model, and panel threshold model, and the following conclusions were drawn: (1) Benchmark regression results showed that both formal and informal environmental regulations effectively promoted the industrial structure transformation and upgrading in cities of the Yellow River Basin. In addition, the effect of informal environmental regulations on industrial structure upgrading was stronger than that of formal environmental regulations, and the regional heterogeneity and temporal stage characteristics were obvious. (2) Both formal and informal environmental regulations affected the industrial structure upgrading in the Yellow River Basin through the mediation of scientific and technological innovation, and the mediating effect was significant. The panel threshold regression results showed that with scientific and technological innovation as the threshold variable, formal environmental regulations have a corresponding relationship with industrial structure upgrading in the Yellow River Basin in the form of a broken line, and the promotion effect of informal environmental regulations on industrial structure upgrading was significantly enhanced after the scientific and technological innovation crossed a certain threshold.This study considered the current industrial structure upgrading trends in the Yellow River Basin and examined the direct effects of formal and informal environmental regulations on industrial structure upgrading in the Yellow River Basin and the indirect effects on industrial structure upgrading through the mediation of scientific and technological innovation.(1)Reasonably increasing the intensity of formal environmental regulations could promote industrial structure transformation and upgrading. The government should strengthen environmental regulations, appropriately increase the intensity of formal environmental regulations, and restrain the pollution emission behaviors of enterprises. In this way, industrial structure optimization can be promoted with environmental regulations while solving environmental problems. Considering the significant regional differences in geographic conditions, resource endowment, industrial structure, and economic development in the Yellow River Basin, it is important to avoid the “one-size-fits-all” approach in the formulation and implementation of environmental regulation policies. Instead, the government should control the strength and timing of formal environmental regulations according to local conditions and seasonal conditions.(2)A diversified environmental governance system must be constructed, and the role of informal environmental regulations in promoting industrial structure upgrading must be emphasized and strengthened. The per capita income level should be raised and synchronized with economic growth. In the meantime, investment in education should be increased, and the level of human capital should be raised to enhance the public’s awareness and ability to act on environmental protection. The government should take measures, such as strengthening environmental protection education and publicity, actively disclosing enterprise information related to environmental protection, improving the environmental protection reporting and petitioning systems, establishing green channels for environmental protection, and rewarding people related to environmental protection and reporting pollution to guide the public to actively participate in environmental protection.(3)In environmental regulation and industrial structure upgrading, maximize the conduction effect of technological innovation. It is important to recognize how science and technology innovation can positively influence formal environmental regulation and industrial structure change, and to avoid squeezing out investment in science and technology innovation while increasing environmental management, and to guide more capital to high-tech industries. By promoting environmental regulation and science and technology innovation, we will promote industrial structure upgrading synergistically, and we will encourage enterprises to use technological innovation as a driving force for transforming traditional polluting industries into high-end, intelligent, and green industries. Developing eco-economy, circular economy, and digital economy as new industries and business models to develop a modern industrial system and upgrade the industrial structure.(4)The government should build a green scientific and technological innovation system and stimulate the vitality of enterprises’ independent research and development. The government should stimulate enterprises’ research and development enthusiasm and improve their independent innovation capability through policies such as financial subsidies, scientific and technological support, patent protection, and perfecting the science and technology investment and financing system. The government should promote the flow of production factors such as capital and talents to science and technology innovation in order to optimize the allocation of production factors and promote the transformation of scientific and technological achievements. The government should also focus on the transformation and upgrading of traditional industries and the development needs of strategic and emerging industries to help the transformation of resource-intensive industries in the Yellow River Basin to technology-intensive industries and clean and environmentally friendly industries, thus promoting the industrial structure optimization and upgrading.


This study presents the routine prosection findings of a 73-year-old male cadaver, with the cause of death reported to be hypertension and respiratory failure. Deep thorax and abdomen dissection exposed profound external and internal anatomical abnormalities. Externally, the body exhibited the following: pectus excavatum; short-limbed dwarfism; and abnormalities of the head, face, and external genitalia. Most of these findings suggest that the donor had Robinow syndrome, a rare genetic disorder involving developmental delay and skeletal abnormalities akin to those found in this cadaver. The internal gross anatomical findings included the following: megacolon; hiatal hernia; bilateral inguinal hernias; laterally displaced right kidney with a fibrous adhesion extending from the inferior pole of the kidney to the inguinal canal; atypical branching of the abdominal aorta; superiorly displaced diaphragm; pulmonary hypoplasia; heart right of midline; and curved esophagus. Although determining the exact etiology of megacolon is difficult in a cadaveric specimen, it is important to investigate the physiological changes associated with it. Therefore, the aim of this study was to investigate the space-occupying pathology of megacolon and to discuss a potential connection between megacolon and Robinow syndrome. Whereas some of the findings in this article were previously presented both as a poster and a podium presentation at the Michigan Osteopathic Association 123rd Annual Spring Scientific Convention , the details herein further explore in depth, the pathophysiology and histopathology underlying the megacolon and other gross pathoanatomical findings in the cadaver presented. Megacolon is defined as acute, toxic, or chronic distension of the large intestine in the absence of mechanical obstruction [The cadaver presented in this article exhibited gross anatomical features of Robinow syndrome and megacolon. This is a unique situation since the database is devoid of any description of the association between the two conditions. Robinow syndrome is a genetic disorder that affects bone development and often manifests as genital deformity or craniofacial abnormalities such as cleft lip/palate ,4. It woPathoanatomical findingsDuring routine dissection of a 73-year-old male cadaver, multiple anatomical variations and abnormalities were discovered. The main observations included the following: megacolon Figure ; bilaterThe colon was dilated, particularly the descending segment, which featured a maximal dilation measuring approximately 23 cm. Comparatively, the enlargements of the cecum, ascending and transverse colon were not as remarkable. The hepatic and splenic flexures were markedly narrowed Figure . In contThe gross anatomic sequelae of megacolon were easy to notice in this cadaver. For example, it was evident that abdominal and thoracic organs had all been shifted to some degree by mass displacements. The diaphragm, heart, and lungs had all been shifted superiorly Figure . PortionThis plethora of internal variations and abnormalities prompted to note external features as well, with the following being most prominent: short stature of approximately 5’1” with relatively short limbs; pectus deformity; webbed penis; wide-set eyes; enlarged tongue; and anteverted nares.Histopathological findingsBecause of the numerous adhesions in the cadaver, the authors wondered if there might have been some involvement of an underlying connective tissue disorder. Sections from various organs stained with H&E and Congo Red were negative for amyloidosis which could have contributed to the organ abnormalities and fibrous pathology. Of note, sections from the left ventricle showed evidence of chronic myocardial fibrosis and muscle atrophy Figure . HistoloThe extensive anatomical variations and abnormalities on this cadaver could not be explained by the limited medical history provided upon body donation, which included hypertension, hyperlipidemia, type 2 diabetes, GERD, seizures, and repeated falls. Further investigation into the medical history and communication with the family confirmed a history of developmental delay since birth. Interestingly, the family also reported episodes of severe constipation for approximately 20 years before death. However, no specific syndromic diagnosis is listed that would explain the thoraco-abdominal and external findings.It is clear that this individual suffered severe megacolon. It is reasonable to believe that the condition was long-standing because of the chronic force required to displace viscera of the abdomen and thorax in such a profound manner as was discovered during prosection. Another indication that this case of megacolon is chronic rather than acute or toxic is supported by the 20-year history of constipation prior to death.Chronic megacolon can be congenital, acquired, or idiopathic . The strModern-day surgical treatments for congenital Hirschsprung disease include low anterior rectal resection and terminal ileostomy, pull-out anterior rectal resection and terminal ileostomy, and low anterior resection. Post-operative course in these cases is most often uncomplicated. After resection, patients either undergo fecal diversion such as colostomy or intestinal continuity restoration such as subtotal colectomy. Possible complications include those typical of any surgery manipulating the bowel, including hypoproteinemia, anemia, obstruction, abdominal effusion, and infection of the surgical incision .Diagnostic capabilities in cadaveric study are extremely limited; a full history and physical examination are impossible to obtain and neither laboratory nor genetic testing is feasible. As such, all attempts of diagnosis using the cadaver are based on anatomic changes that are appreciable post-mortem as well as limited medical history, augmented by information reported by the family.Therefore, the authors relied on anatomical cues for genetic pathology to support the hypothesis that the megacolon was indeed congenital. These included the fetal facial features, short stature, accessory renal arteries, genital deformity, heart defects, and the ligamentous structure extending from the liver, showing embryologic features. With these clues supporting genetic and/or embryologic pathology, Robinow syndrome becomes the most likely diagnosis given the close alignment of symptoms resulting from that disease process and the gross and microscopic findings discovered on this cadaver, namely, short stature, fetal facial features, genital deformity grossly, and left ventricular myocardial fibrosis. There is also a history of developmental delay, which is typically present in cases of Robinow syndrome. Robinow syndrome can result from a variety of gene mutations, and can be autosomal recessive, from a loss of function mutation in the ROR2 gene, or autosomal dominant, from a mutation either to WNT5A or to DVL1 .During routine prosection of a 73-year-old male cadaver, the authors discovered a number of anatomical anomalies that could not be explained by the reported medical history, most notable of which being extensive distension of the descending colon. The anatomical nature of the megacolon and the report from the family indicating constipation 20 years prior to death pointed to a chronic rather than an acute process. The additional internal anatomical variations of accessory renal arteries and atypical fibrous adhesions suggested an underlying congenital cause for these developmental anomalies. These unique external findings narrow that congenital cause to the diagnosis of Robinow syndrome. The nature of cadaveric dissection limits diagnostics, so laboratory and genetic testing were not possible to confirm the diagnosis. Regardless, this case of megacolon in a cadaver illustrates the profound space-occupying effects of megacolon, in that almost every abdominal and thoracic organ was affected in some way due to the sheer size of the defect and consequential mass effect. This highlights the importance of early detection and treatment of megacolon. As for its relation to Robinow syndrome, which is suspected in this cadaver, more genetic research and data would be required to properly correlate megacolon as a feature of Robinow syndrome.


After spinal cord injury (SCI), the destruction of spinal parenchyma causes permanent deficits in motor functions, which correlates with the severity and location of the lesion. Despite being disconnected from their targets, most cortical motor neurons survive the acute phase of SCI, and these neurons can therefore be a resource for functional recovery, provided that they are properly reconnected and retuned to a physiological state. However, inappropriate re-integration of cortical neurons or aberrant activity of corticospinal networks may worsen the long-term outcomes of SCI. In this review, we revisit recent studies addressing the relation between cortical disinhibition and functional recovery after SCI. Evidence suggests that cortical disinhibition can be either beneficial or detrimental in a context-dependent manner. A careful examination of clinical data helps to resolve apparent paradoxes and explain the heterogeneity of treatment outcomes. Additionally, evidence gained from SCI animal models indicates probable mechanisms mediating cortical disinhibition. Understanding the mechanisms and dynamics of cortical disinhibition is a prerequisite to improve current interventions through targeted pharmacological and/or rehabilitative interventions following SCI. Traumatic SCI is a sudden and unpredictable incident that destroys portions of the spinal cord, leading to motor and sensory deficits, as well as dysfunctions of the somatic and autonomic nervous systems . Beyond Many of the neurons that become disconnected following SCI reside outside the spinal cord, such as the motor neurons of the primary motor cortex, which are crucial for the control of voluntary movements. These disconnected neurons are a resource for the long-term regeneration and functional recovery of the central nervous system. However, the axotomy resulting from SCI has an impact on the physiology of the cortical and corticospinal network ,22,23, wFollowing SCI, extensive functional plasticity and the reorganization of neuronal circuits often involve altered inhibitory neurotransmission ,35,36,37Here, we consider the specific patterns of functional cortical derangement after SCI, focusing primarily on works based on TMS. TMS is a technique that evokes neuronal activity by the juxtaposition of magnetic coils to the skull and the generation of magnetic fields, delivered as pulses, in selected and focalized cortical areas. Therewith, evoked electrophysiological activity can be measured from the cortex, spinal cord and muscles targeted by the stimulated motor areas, and specific parameters in the readout reflect the relative excitability and inhibition of cortical and corticospinal circuits ,46. HoweEarly works have suggested that the alteration of inhibitory mechanisms ensues from SCI and causes increased excitability and plasticity in the central nervous system ,58. AccoIndependent evidence converging towards a similar conclusion, i.e., the occurrence of the loss of inhibition after SCI, was obtained by measuring cortical silent periods (CSP). A CSP indicates the duration of the transient decrease in motor neuron excitability after a TMS pulse. SCI was found to shorten the CSP , which cThe works cited so far suggest that disinhibition and increased CNS excitability are beneficial for motor recovery after SCI. However, there is evidence to suggest that cortical disinhibition is detrimental: the exacerbated loss of cortical inhibition and hyper-excitability can lead to maladaptive plasticity and neuropathic pain ,81. For In summary, a complex clinical scenario reveals that the loss of inhibition following SCI can be helpful on one side to intensify the output signal of cortical motor neurons to the spinal cord. On the other hand, excessive disinhibition can also contribute to the development of chronic pain and maladaptive plasticity, and it can hinder motor control . Since dEven though the loss of CNS inhibition is often observed after SCI, it may not be a condition that applies to all patients  nor fullAs a consequence, although not always present, disinhibition may well occur concomitantly with other plasticity mechanisms, resulting in apparent heterogeneity and discrepancy between experimental outcomes ,63,89. FA further example of conflicting outcomes on the matter of cortical disinhibition involves two works based on TMS related to patients with cervical SCI ,64. WherTaken together, studies describing altered balances between cortical excitation and inhibition point towards a relevance of this phenomenon in the course of recovery following SCI. However, many confounding factors need to be addressed to improve the comparability of studies made at different clinical centers. Importantly, the severity and position of injury, as well as the time post-injury, need to be considered in the interpretation of TMS outcomes. Moreover, each patient receives a personalized regimen of pharmacological and rehabilitative treatments that has an impact on their cortical plasticity. Therefore, it is necessary for the field to agree on standardized stimulation protocols and methods of analysis that can enable studies with a larger number of patients and adequate controls.Pre-clinical research helps to define mechanisms that can converge to an altered ratio of excitation and inhibition following SCI and to refine hypotheses about the reasons for phenotypic heterogeneity, as reported in clinical findings. Focusing on molecular “bottlenecks” of inhibitory neurotransmission, the likely mechanisms of cortical disinhibition after SCI are presented in the following section .The synthesis of neurotransmitters, such as glutamate and GABA, demand considerable energy consumption . Of thesMicroglia activation plays a pivotal role in SCI. Furthermore, chronic inflammation seems to affect supraspinal regions as well . This isThe extracellular elements of proteoglycans, known as perineuronal nets, mediate stability in network architecture as well as protection from stress . DismantAxotomy and neuronal trauma perturb the physiology of astrocytes . Trauma A physiological process closely tied to disinhibitory mechanisms is the rewiring of cortical circuits after SCI. Like other injuries involving deafferentation of the central nervous system, SCI involves the rewiring of cortical and subcortical areas, as well as the shift of somatotopic representations and changes in competence of motor areas, which relay on significant events of network plasticity . DecreasB receptor signaling, which controls dendritic excitability via intracellular calcium signaling [Some causes of hyperexcitability may be independent from disinhibition. Nevertheless, solving pathological hyperexcitability may necessitate retuning inhibitory components. For instance, axotomy results in the depolarization and hyperexcitability of cortical principal neurons after SCI . The retignaling . In contignaling . The actignaling . Additioignaling . Thus, nignaling ,136. Sinignaling ,138,139.Since disinhibition is integral to plastic rewiring in the central nervous system ,125,126 The repetition of TMS pulses, delivered to the motor cortex at short intervals, modulate corticospinal excitability and improve motor functions, defined as hand movement and dexterity, in incomplete chronic cervical SCI patients ,140. TheBesides TMS-based therapy, periods of loss of cortical inhibition may be useful windows of opportunity for improving recovery based on increased motor exercises. Essentially, lowered interneuron activity in the cortical circuit may, in some SCI patients, become an asset to boost the outcomes of therapy aiming for motor recovery. Following this idea, robotic training successfully achieved increased smoothness and improved aim of movements in chronic cervical SCI tetraplegic patients who had no likelihood of further movement recovery . In suchAmongst the consequences of SCI on the central nervous system, the loss of inhibition is a common finding, albeit not always observed, and it is likely to fluctuate over time. Changes in cortical excitability involve a plethora of mechanisms, which individual effects may combine in complex and variable outcomes. When reported, the loss of inhibition is mostly proposed to improve motor recovery and can therefore be exploited for that purpose. On the other hand, the loss of inhibition can under some conditions aggravate SCI symptoms in some patients. Thus, the extent of alteration in the balance of excitatory and inhibitory networks should be determined on a patient-to-patient basis and at different times after injury for optimal therapy design. However, this first requires the standardization of assessment methods and the resolution of molecular pathways causing altered cortical dysfunctions in patients after SCI.


The cerebellum has a homogeneous structure and performs different computational functions such as modulation/coordination of the communication between cerebral regions, and regulation/integration of sensory information. Albeit cerebellar activity is generally associated with motor functions, several recent studies link it to various cognitive functions, including spatial navigation. In addition, cerebellar activity plays a modulatory role in different cognitive domains and brain processes. Depending on the network involved, cerebellar damage results in specific functional alterations, even when no function loss might be detected. In the present review, we discuss evidence of brainstem degeneration and of a substantial reduction of neurons in nuclei connected to the inferior olivary nucleus in the early stages of Alzheimer’s disease. Based on the rich patterns of afferences from the inferior olive nucleus to the cerebellum, we argue that the subtle alterations in spatial navigation described in the early stages of dementia stem from alterations of the neuromodulatory functions of the cerebellum. The last decades have been characterized by an impressive body of evidence on the role of the human cerebellum in a wide range of cognitive functions, including perception, language, working memory, executive functions, behavioral control, and social cognition . To dateThe present review examines the extant evidence from animal studies on the role of the cerebellum in spatial navigation. Based on this evidence, we propose that the navigational disorders observed in humans at the early stages of dementia may reflect the neurodegeneration of cerebellar structures involved in navigational cerebro-cerebellar network. Evidence in support of this interpretation comes from clinical studies, indicating that patients with different types of dementia ,3,4,5,6 The review is organized in four main sections as we (1) discuss the visuospatial skills involved in spatial navigation and their neural correlates, we provide an overview (2) of the available evidence on the cerebellar contribution to spatial navigation and (3) on the function of the inferior olivary complex in regulating the cerebellar activity. Finally, (4) we discuss the role of the cerebellum in spatial navigation disorders observed in dementia and propose that they reflect alteration of the network involving connections between the inferior olivary complex and the cerebellum.Spatial navigation represents the individuals’ ability to acquire new environmental knowledge, develop cognitive maps, and determine the correct path to reach a goal using multiple cues, landmarks and beacons . To perfThere are several models of spatial navigation that acknowledge the role of visuo-spatial skills and specify the neural circuits involved. For instance, Byrne et al. (2007) , in the Cognitive models also acknowledge the role of visuo-spatial skills in navigation. For instance, Siegel and White 1975)  propose 75  propoAlthough the function of the cerebellum has typically been associated with motor functions, several recent studies point to the cerebellum being involved in various cognitive functions , includiAlready in 2013, Rochefort  reviewinAn important contribution also comes from a recent study  showing Importantly, the model predicts that lesions in different cerebellum areas should have similar effect on different domains depending on the cerebrellum-brain network affected by the lesion  ,32. IndeThe neural system underlying visuospatial abilities and spatial navigation includes the posterior parietal cortex (PPC) as a central area that is part of a complex, wide network of different brain areas . The posOne is the parieto-prefrontal pathway, which involves lateral intraparietal area (LIP), ventral intraparietal area (VIP), medial temporal area (MT) and medial superior temporal area (MST) that project to the prefrontal cortex. This pathway contributes to the visual processing of information and spatial working memory . The othThe neural architecture involving connections to the posterior parietal cortex is acknowledged by the BBB model , accordiMore specifically, studies using viral tracers in nonhuman primates show a di-synaptic projection from the dentate nucleus (DN) towards the prefrontal cortex, passing through the median-dorsal and ventrolateral nuclei of the thalamus . This suClinical studies also provide some converging evidence. For example, Tedesco et al.  tested nTo sum up, that the cerebellum plays an important role in many cognitive, sensorimotor, and behavioral functions is well accepted. In contrast, the role of the cerebellum in human navigation has been less explored despite evidence from animals’ studies ,51 consiThe inferior olive (IO), together with the pontine nuclei, represents the primary afferences to the cerebellum. Alterations in the activity of the inferior olive should result in alterations of cerebellar activity and consequently, of the activity in the cerebral areas to which the cerebellum is connected (and whose activities are modulated by cerebellum), including those responsible for the cognitive processes of spatial navigation.The inferior olivary complex (IO) is an ovoidal grey matter region located in the medulla oblongata, the ventral part of the brainstem. Its anatomical position is near the lateral posterior furrow, where the hypoglossal, glossopharyngeal, vagus and accessory nerves emerge . IO formTwo main types of neurons are found in the principal olive: the large multipolar excitatory neurons (90% of the PO cells) and the small inhibitory interneurons (10% of the PO cells). The large multipolar excitatory neurons are glutamatergic cells with long axons, that extend rostrally from the nucleus to form the climbing fibers that, in turn, project to the contralateral cerebellar cortex. Furthermore, these axons send collateral fibers to the dentate nucleus. Principal olive neurons act as an electrical syncytium due to the presence of gap-junctions, which constitute dendro-dendritic electrical synapses. Each principal olive neuron is electrically coupled with about fifty neighboring neurons and discharges rhythmically and synchronically with them ,57.The principal olive receives projections from different brain areas . The gluThe prominent inhibitory projections (GABAergic) to the principal olive start from the parvocellular part of the red nucleus, basal ganglia and dentate nucleus (DN) ,66,67,68The outputs of the principal olive are the climbing fibers (CFs). These fibers pass into the restiform body projecting to the cerebellar cortex and, concurrently with the mossy fibers (MFs), represent the principal inputs to the cerebellar cortex, very likely playing a pivotal role in modulating cerebellar activity. A single climbing fiber carries impulses at frequencies lower than 10 Hz and innerves a single adult Purkinje cell  with multiple excitatory synapses. CFs axon terminals wrap around the Purkinje cells body and proximal dendrites in multiple points ,71. A clBased on the motor cerebellar-cortical forward computational model  that speBased on the architectural connections of the IO, several studies suggest that IO is involved in the ability to detect stimuli synchronicity that lay at the basis of spatial navigation functions ,74,75. TSimilarly, Ito , suggestEvidence about the involvement of olive-cerebellar system activity in the spatial navigation also comes from lesion studies on animals. Following unilateral transection of the inferior cerebellar peduncle (pedunculotomy), which unilaterally interrupts the olivo-cerebellar pathway, reinnervation occurs from the remaining peduncle towards the denervated hemi-cerebellum in new-born rats, but not in animals who received the pedunculotomy 11 days from birth, that, due to this lack of reinnervation, show severe deficits in spatial navigation tests, such as the water maze. Compared to controls, rats with later pedunculotomy do not show spatial learning and even after several trials are not able to perform direct journeys to reach the platform. In contrast, animals with pedunculotomy at birth, that have completed the reinnervation process, are able to learn the position of the platform, although less effectively than controls, and show difficulties in maintaining memory from one day to the next ,80,81.To sum up, there is evidence that the IO plays a crucial role in monitoring and modulating the cerebellar cortical circuit. Based on this evidence a possible specific role of IO in processing the timing components of navigational inputs has been suggested. Next, we are discussing the early signs of navigation deficits observed in different types of dementia as due to the likely involvement of the IO in the neurodegeneration of the cerebellar cortical circuit.In the early stages of the disease, patients with different types of dementia–Alzheimer’s disease ,3,4,5,6,According to Aguirre and D’Esposito  topograpEgocentric disorientation and heading disorientation seem to characterize the episodes of topographical disorientation that are described in dementia, sometimes as the very first symptom. However, some recent studies underline the possibility that these deficits are preceded by anterograde disorientation. More specifically, Bianchini  report aIndeed, Alzheimer’s disease neuropathology, both at the early or preclinical and asymptomatic stages, is strongly related to brain atrophy in areas that are part of the spatial navigation network, including the medial temporal lobe and more specifically the entorhinal cortex, perirhinal cortex and hippocampus . This enFurthermore, a resting state functional magnetic resonance imaging (fMRI) study  providesAs a final remark, it is also worth noting some similarity between symptoms shown by patients with dementia and symptoms shown by patients with Cognitive Cerebellar Affective Syndrome (CCAS), a pathological condition that can be referred to as a constellation of deficits in the cognitive domains of executive function, spatial cognition, language, and affective regulation, resulting from damage to the cerebellum ,107. In To sum up, our hypothesis is that, a cerebellum dysfunction due to the neurodegenerative pathology in Alzheimer’s disease may be partially responsible for the early appearance of emotional and affective disorders, caused by functional disconnections due to the malfunctioning of some nodal nuclei. Based on the evidence above discussed, we argue that among the cerebellar nuclei, the inferior olive, which plays a primary role in the updating of plastic cerebellar models  can be iPhysiological and neuroimaging studies show a high correlation between the olivo-cerebellar system activity, the brainstem structures, and the cortical areas responsible for visuospatial functions. The interaction among these neural structures is responsible for the dynamicity of updating processes in models of motor activity and cognitive functions over time. This function is essential for processes that operates a continuous update of the individual position in the environment–like path integration–mainly based on processing idiothetic information about an individual’s movements in the environment. It is also very important for processing the metric features of the environment, since by processing times, it contributes to the evaluation of distance between different points of the environment. Thus, the olivo-cerebellar system and the connected cortical circuits may represent an essential hub involved in communication between different brain areas during the acquisition and the retrieval of environmental information for navigational purposes.Indeed, some studies point to the primary role of the inferior olive-cerebellar system in coding temporal information, regardless of motor behaviour. Temporal coding plays an important role in learning and representing environments, especially complex ones, as well as in planning a route and monitoring the correctness of navigation. It is possible that the role played by olive-cerebellar system in navigation consists in processing the temporal components of environmental representation and navigation. Therefore, the altered processing of temporal information attributable to a dysfunction of this system should correspond to altered ability to learn environments  as well the ability to monitor navigation, making individuals not able to compute distance in relation to the speed of their translations. Measuring the relation between time processing and visuospatial abilities could allow to better understand navigational processes and the underling neural network, allowing also to develop novel ways for early detection of preclinical signs of neurodegenerative disorders.


Bidirectional cross-talk between commensal microbiota and the immune system is essential for the regulation of immune responses and the formation of immunological memory. Perturbations of microbiome-immune system interactions can lead to dysregulated immune responses against invading pathogens and/or to the loss of self-tolerance, leading to systemic inflammation and genesis of several immune-mediated pathologies, including neurodegeneration. In this paper, we first investigated the contribution of the immunomodulatory effects of microbiota (bacteria and fungi) in shaping immune responses and influencing the formation of immunological memory cells using a network-based bioinformatics approach. In addition, we investigated the possible role of microbiota-host-immune system interactions and of microbiota-virus interactions in a group of neurodegenerative diseases (NDs): Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), Parkinson’s disease (PD) and Alzheimer’s disease (AD). Our analysis highlighted various aspects of the innate and adaptive immune response systems that can be modulated by microbiota, including the activation and maturation of microglia which are implicated in the development of NDs. It also led to the identification of specific microbiota components which might be able to influence immune system processes (ISPs) involved in the pathogenesis of NDs. In addition, it indicated that the impact of microbiota-derived metabolites in influencing disease-associated ISPs, is higher in MS disease, than in AD, PD and ALS suggesting a more important role of microbiota mediated-immune effects in MS. Gut microbiota play an essential role in maintaining homeostasis in the human host, with more than 100 trillion microorganisms  colonizing our gastrointestinal (GI) tract . These mvia the production of microbiota-derived bioactive molecules, such as short-chain fatty acids (SCFAs) and neurotransmitters (NTs)  , 11. Howrs (NTs) .Perturbations of the microbiome-immune system cross-talk due to microbiome-host dysbiosis can lead to the dysregulation of immune responses against invading pathogens and/or the loss of self-tolerance, leading to systemic inflammation and the genesis of several immune-mediated diseases. Perturbations of microbiome-host symbiosis, resulting in dysbiosis, can be caused by both environmental and genetic factors. However it is believed that the environmental-mediated perturbations outweigh host genetic polymorphism-mediated perturbations in shaping microbiome-host interactions .Importanvia perturbations of the microbiota-brain-gut axis -immune system interactions might facilitate the development and/progression of several NDs.In this paper, we extend upon the methodology developed in our previous work  and use Our pipeline approach consists of the following steps: (A) Collection from well-known Data Sources, (B) Network Reconstruction and Enrichment Analysis, (C) Similarity-Based Analysis, (D)Network Topology Analysis, and (F) Network Re-Wiring Analysis. To investigate the effects of microbiota-derived metabolic products on ISPs we first mined the Human Metabolome Database (HMDB) (version 4.0)  to colleMetaboAnalyst tool (version 5.0)  , that prion 5.0) . Then weTRING: disease query of the StringApp in Cytoscape, which is a network visualization and analysis tool . Then the enriched GO ISPs terms were merged with the microbiota-to-metabolite associations obtained from the HMDB database, in order to construct the MMI network. To model the immunomodulatory effects of microbiota-derived metabolites produced by bacteria and fungi, we constructed a microbiota - metabolites -Gene Ontology Immune System Processes (GO ISPs) network, called MMI network, using age in R . The conage in R  in CytosTo identify disease-associated genes that can be modulated by microbiota components in each of the four NDs , we merged the microbiota-metabolites-genes interactions, collected in Section 2.1 (i), with each of the 200 disease-associated genes of these diseases. For each of the four NDs we then constructed a microbiota-metabolites-ND associated genes- GO ISPs (MMDI) network. More specifically, to create the four MMDI networks we first performed enrichment analysis on the 200 disease-associated genes for each of the four NDs, using the same parameters as in the enrichment analysis performed in part (i). Then we merged the microbiota-metabolites-genes interactions with the ND-associated genes and the ND siginificantly enriched GO ISP terms, allowing to construct the four MMDI networks. Then for each of the four MMDI networks we only retained microbiota components and metabolites that interact with the ND-associated genes. This allowed to identify microbiota components which produce metabolites that target genes associated with these diseases and therefore can modulate ND-associated GO ISPs. The characteristics of each of the four MMDI networks are described in To investigate the possible contribution of microbiota - virus interactions in the development of NDs, we used the case of EBV, which has been associated with the development of three out of the four selected NDs, namely AD, MS and PD –49. The In order to identify the immunomodulatory effects of EBV in the three remaining NDs, we merged the EBV-host PPI network with each of the 200 disease-associated proteins (from the corresponding genes), resulting in the construction of three integrated EBV-ND PPI networks. Then we performed enrichment analysis on the human protein targets of EBV and their first neighbors, extracted from each of the three integrated EBV-ND PPI networks. The human proteins used to perform enrichment analysis were 1392, 1389 and 1381 for AD, PD and MS respectively.vegan package in R  metabolites and GO ISPs, (B) microbiota and GO ISPs and (C) microbiota and metabolites, illustrated in age in R  we measuage in R  we perfohttps://c-big.shinyapps.io/list2net/), a shiny application created by our group, that transforms lists of data to networks based on pairwise commonalities. Therefore, within the network, a microbiota component is connected with an edge with another microbiota component based on the common metabolites they produce. The weight of each edge is the sum of the common metabolites between each two connected microbiota components. The application also provides network metrics of various topological analysis measures, including degree and strength centralities. The degree centrality indicates the number of connections between two microbiota components and it was used to identify the microbiota components that have the highest number of associations with other microbiota components. The strength centrality, indicates the sum of the weights of all the links each node has and it was used to identify the Top 10 microbiota components with the highest potential to exert synergistic ISP effects. In addition, List2Net also provides other network metrics, such as identifying articulation points within the network whose removal will disconnect the largest connected microbial module within the network into several smaller modules. The articulation points metric was used to identify microbiota components within the network whose presence was important for ensuring network connectivity.Microbiota components that produce the same metabolites influence the same ISPs and thus have the same effects on those processes. Thus, we used the direct relationships of microbiota components and their metabolic products, We used a Venn diagram, to compare the 53 EBV significantly enriched GO ISP terms obtained from the EBV-host PPI network with the 120 GO ISP terms associated with microbiota from the MMI network. The comparison revealed 24 common GO ISPs that can be modulated by EBV and microbiota components. The number of the microbiota components that co-modulate with EBV these 24 GO ISPs was found to be 241. Similarity-based analysis was performed between the 241 microbiotas and EBV based on their similarity to modulate the 24 common GO ISPs, by using the same methodology as in part (i). The similarity-based analysis was used to arrange the 241 microbiotas based on how similar or dissimilar immunomodulatory effects they had in respect to these 24 common GO ISPs with EBV.In addition, we compared the EBV significantly enriched GO ISPs per disease  with the GO ISPs that have been identified to be modulated by microbiota components in the corresponding MMDI networks identified in Section 2.2 parts (ii) and (iii). This allowed to identify ND-associated GO ISPs that can be modulated by both microbiota components and EBV.DyNet app in Cytoscape which allows to visualize and analyze dynamic changes in molecular interactions in multi-states , and the production of autoantibodies .Furthermore, 1.64% of the terms belong to the group of microglia cell activation, which are considered as the resident macrophages of the CNS and play an important role in inflammation and infection within the brain . TherefoThe agglomerative hierarchical clustering of the 93 microbiota-derived metabolites that interact with the 542 genes that are associated with the 120 GO ISPs, indicated the presence of 14 clusters of metabolites based on similarity of GO ISP effects, shown in Whereas, contrary to formic acid and proprionic acid, acetic acid which is also an SCFA, belongs in a distant cluster, inidicating dissimilar immunomodulatory effects between acetic acid and these two SCFAs. Disimilar effects can also be seen between L-lactic acid and its harmful enantiomer D-lactic acid, where the former is in the same cluster as 4-hydroxcinammic acid and the neurotransmitter phenylethylamine. Whereas, D-lactic acid is in a distant cluster and exert similar effects with the metabolites hydrocinammic acid, which is a carboxylic acid, and tyrosol, which is a phenolic antioxidant compound that can be found in natural sources, such as wine an virgin olive oil.Moroevoer, the clustering results indicated that several metabolites can exert exactly the same immunomodulatory effects, such as the SCFA formic acid which exerts exactly the same ISP effects as flutaric acid. Exactly the same immunomodulatory effects can also be observed between the metabolites phenol, glycolic acid and ascorbic acid, also known as vitamin C.via their metabolic products. This suggests that groups of microbiota can influnce the same ISPs, however it does not necessarily mean that their effect on these processes is the same as they might Interact with different genes. Therefore, the composition of the metabolites they produce and their respective gene targets will determine the outcome of the interaction between a microbiota and an ISP, resulting in its activation or inhibition.Furthermore, the agglomerative hierarchical clustering results of the 256 microbiotas based on GO ISP terms similarity indicated the presence of 14 clusters. The results of the agglomerative hierarchical clustering can be found in via similar mechanisms through their metabolic products, resulting in synergistic immune mediated effects. In addition, based on the constructed network, only 6 microbiota components produce unique metabolites. The network is also composed by two small connected microbial modules. The first one contains only methane producing bacteria, known as methanogens, thus these microbiota components modulate the immune system in the same way. The second microbial module contains two Lactobacillus species, the Lactobacillus plantarum and Lactobacillus paracasei, where they share 1 metabolite that is not shared by other microbiota components.To identify modules of microbiota that produce the same metabolites and thus affect the same ISPs, we created a microbiota-to-microbiota associations network  based on pairwise similarity of the 72 metabolites the 256 microbiotas (genera/species/strain) produce. Visualization of the network indicated that the majority of microbiota components produce at least one metabolite that is also produced by another microbiota component, forming a large connected microbial module. This suggests that several pairwise groups of microbiota components can modulate ISPs Clostridium beijerinckii species, Pseudomonas putida species, Micrococcus genus, Klebsiella genus, Pseudomonas fluorescens species, Escherichia coli species, Lactobacillus genus, Corynebacterium glutamicum species and Alcaligenes genus. Articulation points are nodes within the network, whose removal will disconnect the largest connected microbial module into several smaller modules, thus these microbiota components are essential for ensuring network connectivity. Some of the identified articulation points are known opportunistic pathogenic organisms, such as Escherichia coli species, Klebsiella genus, Alcaligenes genus and Pseudomonas putida species. Whereas, other articulation points, such as Lactobacillus genus, are known beneficial gut microbiota, which are also found in probiotic supplements. Pseudomonas fluorescens species, which act as an articulation point, reside in low levels in various body sites and are considered non- pathogenic. However, they can cause acute opportunistic infection in rare occasions, and interestingly they have been associated with the development of Chron’s disease  and because EBV is a well-studied virus that has lots of available PPI data.Both microbiota and viruses have the ability to influence ISPs, with microbiota exerting their immunomodulatory effects Roseburia genus, Lactobacillus genus, Hansenula polymorpha species, Faecalibacterium prausnitzii species, Eubacterium genus, Coprococcus comes species, Coprococcus eutactus species, Anaerostipes genus and Baccillus genus. Lactobacillus are considered as “friendly” bacteria that live symbiotically within the human host exchibiting health promoting effects and protect against pathogenic organisms . Then, to identify GO ISPs that can be modulated by EBV in each of the three NDs, we performed enrichment analysis on the human protein targets of EBV proteins and their first neighbors in each of the integrated EBV-ND PPI networks. The enrichment analysis of EBV PPI in NDs, indicated that the number of significantly enriched GO ISPs that can be modulated by EBV in MS disease states are 235, in PD state are 87 and in AD state are 99.Then we compared the EBV GO ISP enriched results in the three NDs, with the GO ISPs that can be modulated by microbiota components in the three ND states, which allowed to identify for each ND state the GO ISPs that can be modulated by both microbiota components and EBV. The comparison between the immunomodulatory effects of EBV and microbiota in MS disease, indicated that 169 MS-associated GO ISPs can be modulated by both microbiota components and EBV. Similarly, comparison of the immunomodulatory effects of EBV in PD and AD diseases with the immunomodulatory effects of microbiota on the GO ISPs associated with these disease states, indicated 18 and 36 common ISPs that can be modulated by both microbiota components and EBV, respectively. These results indicate that in MS there is a higher number of disease-associated ISPs that can be modulated by both microbiota and EBV infection, than in PD and AD. Therefore, it is possible that microbiota-EBV interactions, in terms of their immunomodulatory effects, might play a more significant role in MS pathogenesis rather than PD and AD.In this study we performed a network-based bioinformatics approach with the aim to first investigate the immunomodulatory effects of microbiota (bacteria and fungi) through their metabolic products. We also explored how various microbiota components, through their immunomodulatory effects, might be able to influence ISPs associated with NDs, and thus possibly contribute to their development and/or progression. In addition, we explored the immunomodulatory effects of EBV, which is associated with the development of the three NDs, MS, AD and PD, both in general and ND specific states. Moreover, we examine how microbiota-virus interactions might contribute to the modulation of ISPs associated with pathogenic mechanisms involved in NDs. Our network-based methodology is summarized in Statistically significant enrichment analysis revealed 120 GO ISP terms that can be modulated by 93 microbiota-derived metabolites through their interaction with 542 human gene targets. The GO ISPs results, In addition, 7.38% of the enriched terms belong to the group of myeloid leukocyte differentiation. Myeloid cells are important in mounting effective inflammatory responses during viral infections . TherefoMoreover, 14.75% of the GO ISP terms belong to the group of complement activation, classical pathway, which plays an important role in innate immune system defenses against pathogens and also complements antibody responses against pathogens by the adaptive immune system. The complement system also plays a critical role in commensal microbiota-immune system symbiosis and health homeostasis. Improper complement system recognition of commensal microbiota as pathogenic would lead to excessive immune responses and hence to the emergence of immune-mediated diseases , 61. TheThe enrichment analysis results also indicated that microbiota can affect the formation of memory B and T cells by modulating the signaling pathways that are involved in the differentiation of B and T cells, as 11.48% of the GO ISPs terms belong to the group of antigen receptor-mediated signaling pathway. In addition, the enrichment results indicated that microbiota can affect humoral immune response mediated by circulating immunoglobulin. This suggests that microbiota can affect antibody production. This is supported by evidence that indicates that gut commensal microbiota can affect the production of IgA, and the production of autoantibodies , 65. Evivia the production of SCFAs  metabolites and GO ISPs, (b) microbiota and GO ISPs and (c) microbiota and metabolites, illustrated in Ruminococcus genus. This suggests that pathogenic bacteria by producing several metabolites that can be also produced by other microbiota components are able to influence multiple ISPs effects. This also allows them the potential to exert synergistic immunomodulatory effects with other microbiota components, which possibly provides them with increased survival and pathogenicity. The potential of synergistic actions between microbiota components through their metabolic products can possibly affect the immune responses towards the emergence of a specific immune system phenotype. This can occur when there is either an increase or a decrease in the abundance of microbiota components that produce the same metabolite. However, the outcome of the immunomodulatory effects influenced by commensal microbiota composition is not only determined by the combinatorial action of their synergistic relationships, but also by their antagonistic relationships. The metabolites produced by one microbiota component can have an opposite effect on the host’s ISPs compared to the effect of the metabolic products produced by another microbiota component, thus leading to the emergence of antagonist relationships.In addition, the clustering results also indicated that groups of microbiota can influnce the same ISPs. However it does not necessarily mean that by targeting the same ISP the outcome of their effect would be the same as they might interact with different genes in these ISPs, thus leading to either inhibition or activation of the ISPs. Therefore, in order to identify microbiota that have the same outcome on an ISP and thus possible synergistic effets, we extracted from the MMI network the direct relationships between microbiota and metabolites, via their metabolic products might influence pathologies associated with NDs, via their metabolic products. In addition, it allowed to identify intersection nodes which are associated with GO ISPs in these four ND states, The reconstruction and visualization of microbiota-host-interactions in NDs , allowed to identify mechanisms by which microbiota components However, although these four NDs share common microbiota and metabolites it does not mean that the immunomodulatory effects of these microbiotas are the same in these diseases as network dynamics change, due to the emergence of new interactions and nodes that stem from the disease pathology. This “re-wiring” between molecular interactions due to the presence of a disease state is also expected to change microbiota-host interactions. We investigated network re-wiring of the immunomodulatory effects of microbiota between the four NDs  by performing pairwise network comparison which allowed to identify nodes and edges that differ between two network pairs of NDs, Finally, to investigate the possible contribution of microbiota-virus interactions in the development of NDs, we explored whether microbiota that have immunomodulatory effects can modulate similar ISPs as EBV which is associated with the development of three NDs: AD, PD and MS. To investigate the possible presence of microbiota-EBV interactions in modulating GO ISPs associated with NDs, we first constructed three integrated EBV-ND PPI networks, where the EBV-host PPI network was enriched with the disease-associated proteins of each of the three NDs . The enrichment analysis of EBV PPI interactions in NDs, indicated 235, 87 and 99 significantly enriched GO ISPs that can be modulated by EBV in MS, PD and AD states, respectively. Comparison of the EBV GO ISPs results in the three NDs, with the ISPs that can be modulated by microbiota components in the three NDs states, allowed to identify for each ND the ISPs that can be modulated by both microbiota components and EBV. The comparison results indicated that 160 GO ISPs associated with MS disease can be modulated by both microbiota components and EBV, whereas only 18 and 36 GO ISP can be modulated in PD and AD, respectively. This possibly indicates that microbiota-virus immunomodulatory-related interactions, might play a more significant role in MS disease pathogenesis rather than in the pathogenesis of PD and AD.In this paper, we provided a bioinformatics insight approach that tries to capture the effects of microbiota, bacteria and fungi, in shaping immune responses and influencing the formation of immunological memory cells through their metabolic products, under ND states and under ND states with EBV viral infection. We recognize that our study might have certain limitations mainly based on the completeness and the possible biases of the databases used, however despite these limitations our approach allowed us to formulate the following conclusions.The enrichment analysis of microbiota-host interactions allowed to highlight various aspects of the innate and adaptive immune response systems that can be modulated by microbiota, which includes responses during inflammatory triggers. The results also indicated that microbiota can influence the activation and maturation of microglia which are implicated in the development of NDs.Escherichia coli and Klebsiella genera, that can produce several metabolites that are also produced by other microbiota components, allowing them to influence multiple ISPs and thus possibly contributing to their pathogenicity.The reconstruction of the microbiota-to-microbiota associations network based on pairwise similiarity of pairs of microbiota components that can produce the same metabolites allowed to possibly identify a potential of synergestic immunomodulatory actions between microbiota components. The pairwise similarity also indicated that known pathogenic bacteria, such as the Investigation of possible microbiota-host-immune system interactions in NDs allowed for the isolation of specific microbiota components and metabolic products that interact with disease-associated genes that participate in ISPs. The results also suggest that the impact of microbiota-derived metabolites in influencing ISPs is higher in MS, than AD, PD and ALS.Finally, investigation of the possible contribution of microbiota- virus interactions in the development of NDs, allowed to identify ISPs that can be modulated by both microbiota components and EBV. The result of the analysis also suggests that the combinatorial action of the immunomodulatory effects of microbiota-EBV interactions might play a more significant role in MS disease pathogenesis rather than in the pathogenesis of PD and AD.https://hmdb.ca/downloads, PHISTO https://phisto.org/, VirHostNet https://virhostnet.prabi.fr/, DISEASES https://diseases.jensenlab.org/Search.The in-house developed HMDB parsing R script can be provided upon request to the authors.Publicly available datasets were analyzed in this study. This data can be found here: HMDB AO and GS have contributed to the conceptualization, methodology, review and editing of the manuscript. AO collected and analyzed the data, and wrote the original draft manuscript, under the supervision of GS. All authors have contributed to the article and have read and agreed to the published version of the article.This study received support from the Cyprus Institute of Neurology & Genetics and funded by Telethon.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.


Periodontal disease is a significant global health burden affecting half of the world's population. Given that plaque and inflammation control are essential to the attainment of periodontal health, recent trends in preventive dentistry have focused on the use of behavioral models to understand patient psychology and promote self-care and treatment compliance. In addition to their uses in classifying, explaining and predicting oral hygiene practices, behavioral models have been adopted in the design of oral hygiene interventions from individual to population levels. Despite the growing focus on behavioral modification in dentistry, the currently available evidence in the field of periodontology is scarce, and interventions have primarily measured changes in patient beliefs or performance in oral hygiene behaviors. Few studies have measured their impact on clinical outcomes, such as plaque levels, gingival bleeding and periodontal pocket reduction, which serve as indicators of the patient's disease status and quality of oral self-care. The present narrative review aims to summarize selected literature on the use of behavioral models to improve periodontal outcomes. A search was performed on existing behavioral models used to guide dental interventions to identify their use in interventions measuring periodontal parameters. The main models were identified and subsequently grouped by their underlying theoretical area of focus: patient beliefs ; stages of readiness to change ; planning behavioral change ; and self-monitoring (self-regulation theory). Key constructs of each model and the findings of associated interventions were described. The COM-B model, a newer behavioral change system that has been increasingly used to guide interventions and policy changes, is discussed with reference to its use in oral health settings. Within the limitations of the available evidence, interventions addressing patient beliefs, motivation, intention and self-regulation could lead to improved outcomes in periodontal health. Direct comparisons between interventions could not be made due to differences in protocol design, research populations and follow-up periods. The conclusions of this review assist clinicians with implementing psychological interventions for oral hygiene promotion and highlight the need for additional studies on the clinical effects of behavioral model-based interventions. Periodontal conditions affect a significant proportion of the world's population, with severe periodontitis affecting 1 in 7 globally . DespiteWhile much of traditional oral hygiene education involves telling the patient what to do, why one should engage in such behaviors, and how they should be performed, this one-sided transfer of information often fails to consider the patient's perspective. Reviews of dental education programs found that most interventions achieved short-term improvements in oral health knowledge but failed to produce long-term behavior changes and clinical improvements in periodontal health . Rather Studies have yet to identify an association between knowledge of nutritional guidelines and actual consumption of the recommended foods , 9. SimiTo understand the components of behavioral change, various models in the field of psychology have been proposed which have been applied and studied in settings ranging from smoking cessation to dietary change , 12. In While there is evidence to support the use of interventions to increase the frequency of oral hygiene behaviors, the clinical implications of this increased performance are less clear . In clinThe objective of this study is to give an overview of the key concepts in behavioral change theory-based interventions and their usefulness in clinical care, ultimately facilitating the future delivery of effective oral hygiene instruction to improve patient motivation, compliance and adherence.The Health Belief Model (HBM) proposed by Rosenstock in 1966 is one of the earliest theories of health behavior and amongst the most widely used . The autIn the past decade, multiple randomized controlled trials of OHI based on the HBM have been conducted. Jeihooni, Jamshidi  noted a As for clinical outcomes, a study involving 34 Chinese adults with periodontitis found that those who received an additional HBM intervention had significantly lower full mouth plaque and bleeding scores than those who received oral hygiene instruction alone . SimilarGiven the importance of establishing good oral habits from a young age, OHIs have frequently been used in child and adolescent populations. In a randomized controlled trial involving 1,159 adolescents in Hong Kong, those receiving OHI based on the HBM had a statistically significant decrease in visible plaque index after 12 months, compared to the control group who received informational booklets on oral hygiene . ImproveAlthough not strictly a model, cognitive behavioral theory (CBT) has been included in reviews of psychological approaches used to guide behavioral change interventions with promising results , 15, 32.Schensul, Salvi  investigThe Stages of Change Model (SCM), also known as the Transtheoretical Model, was proposed by Prochaska and DiClemente . It viewBetter oral hygiene has been found in individuals at more advanced stages of change in the SCM, with decreases in the plaque and gingival indices corresponding with the progression to a higher stage of change . The SCMMotivational interviewing (MI) can be used to assist in the determination of the patient's stage of readiness in the SCM and identify progression over time in order to plan the appropriate oral health education. MI respects the patient's autonomy and individuality, acknowledging that those who are not ready to change are less likely to respond favorably to oral hygiene instruction, and has been found to be effective in improving clinical periodontal parameters in systematic reviews , 46.The Precaution Adoption Process Model (PAPM) from Weinstein is another model that describes the process of behavioral change in a series of stages. Compared to the SCM, the PAPM provides additional insight into patient's level of readiness as it differentiates seven stages of behavioral change: (1) unawareness of the importance of the behavior, (2) aware but unengaged, (3) accepts the issue and deciding about acting, (4) accepts the issue but decides not to change the behavior, (5) accepts the issue and decides to act, (6) takes action to change behavior, (7) maintenance .via plaque disclosing agent, compared to the control. In a randomized controlled trial of 244 adolescents, subjects in the test group were identified based their stage of readiness according to the PAPM . Those aWhile the SCM categorizes its preliminary stages based on an individual's level of intention to act, the Theory of Planned Behavior (TPB) concentrates on the intention itself. The theory, proposed by Ajzen  posits tAn OHI based on the TPB, in which the intervention group received didactic teaching and individual discussion on TPB constructs, resulted in significantly increased perceived behavioral control, flossing behavior, and reduced bleeding on probing . Other lTo address the limitations of the TPB, the Health Action Process Approach (HAPA) model was developed to include the role of planning in transforming intention into subsequent behavioral change. The HAPA consists of a goal-setting (“motivation”) phase and a goal-pursuit (“volition”) phase . A meta-Four randomized controlled trials involving adolescents –62 invesIn addition to the setting of goals through action planning, OHIs have frequently incorporated self-monitoring to facilitate the patient's assessment of their own behavior in relation to their goals . As the Self-regulation theory, which has been defined as the ability to “plan, monitor and direct behavior in changing situations” , involveSelf-evaluation involves comparing the initial goal to the current state, as observed by self-monitoring. Self-reaction consists of an emotional response depending on the extent to which the goal has been achieved, as well as “self-efficacy expectations”, which result in judgments about future capability to perform the required behavior and achieve goals . For exaRandomized controlled trials have demonstrated that self-monitoring of oral hygiene behaviors in patients leads to improved oral hygiene through improved self-care habits , 67, lowDespite a multitude of existing behavioral change models, their infrequent utilization in designing new interventions led to the development of the Capability, Opportunity, Motivation-Behavior model (COM-B), a new model proposed by Michie et al. . In addiAs one of the more recent behavior change models, COM-B has been to identify the facilitators and barriers of behavioral change in smoking cessation , dietaryFurther study of how the application of the COM-B model impacts periodontal health parameters is needed to gauge its clinical success in dental settings. Such interventions would ideally first diagnose which of capability, opportunity or motivation need to be improved in the patient, then induce behavioral change by targeting the specific components involved. To improve psychological capability, provision of traditional dental education through demonstrations can boost knowledge of oral hygiene techniques and their importance. Physical capability could be managed by referral to a medical practitioner or physiotherapist, or through the provision of specially adapted tools such as an end-tufted single head brush or electric toothbrush. Opportunity could be addressed by planning ways to overcome the existing barriers, such as finding a private restroom at one's workplace to create a physical space to carry out the oral hygiene behavior, creating calendar reminders, or involving social support from family and friends. Motivation can be enhanced by transforming patient beliefs through the use of cognitive behavioral therapy and motivational interviewing Asimakopoulou et al.  suggesteThe need for patient cooperation in the management of periodontal diseases has long been acknowledged. Growing awareness of the important role that behavior plays in oral health education and the current limited understanding of how theories can be put into clinical practice have led to calls for further studies on theory-based interventions, particularly on recently developed models such as COM-B.Behavioral change interventions based on several psychological theories were used to improve oral hygiene and periodontal health. It is difficult to draw direct comparisons between interventions due to heterogeneity in constructs, methodology, strength of evidence and standards of reporting. The extent to which each intervention was based on its underlying behavioral change theory could not be accurately determined, with some interventions incorporating aspects from multiple theories , 38, 82.Despite the theoretical and methodological differences between the interventions, a commonality they all share is the use of an evidence-based theoretic framework to understand the constructs of behavior and the development of measures to evaluate these constructs. Compared to conventional dental education, theory-based interventions consider the patient's beliefs, cognition, self-efficacy, level of readiness and socio-environmental context in the delivery of oral health instruction . This re