Gravity determines shape of body tissue and affects the functions of life, both in plants and animals. The cellular response to gravity is an active process of mechanotransduction. Although plants and animals share some common mechanisms of gravity sensing in spite of their distant phylogenetic origin, each species has its own mechanism to sense and respond to gravity. In this review, we discuss current understanding regarding the mechanisms of cellular gravity sensing in plants and animals. Understanding gravisensing also contributes to life on Earth, e.g., understanding osteoporosis and muscle atrophy. Furthermore, in the current age of Mars exploration, understanding cellular responses to gravity will form the foundation of living in space. Gravity also plays crucial roles in cellular function. For example, plants grow leaves and roots in the correct direction by sensing gravity2. Animals regulate the densities of bones and muscles in response to gravitational load4. A response to gravity is an active activity inherent to the physiology of plants and animals.Gravity defines the morphology of life on Earth. It affects the growth and development of plants and animals by regulating the proliferation of their constituent cells6, discussions regarding bone loss and muscle atrophy in microgravity environments are inevitable. This paper also summarizes the recent findings in this field. Through these discussions, we outline the common mechanisms of gravity sensing in plants and animals.Historically, elucidation of gravity sensing mechanisms in life originates from the study of plants. Abundant research in plant biology has laid the foundation for studying gravity sensing mechanisms in animals. In the first half of this article, we review the mechanisms of gravity sensing in plants from the viewpoint of cellular and molecular biology. Subsequently, the mechanisms of gravity sensing in animal cells will be discussed. Since both lunar base construction and manned Mars exploration plans are being discussed at presentThis paper expands on our understanding of gravity sensing in plant and animal cells and discusses the future direction of gravitational biology, with the ultimate purpose of contributing to the development of living in space.The survival of sessile organisms, such as plants, depends upon their ability to avoid or mitigate various environmental stresses to which they are subjected. As one of such strategies, plants possess an ability to control directional growth by gravitropism Fig. . Typical7. A high level of auxin results in forming a complex of the transcriptional repressor, Aux/IAA, and the AUXIN SIGNALING F-BOX PROTEIN co-repressor/auxin receptor, TIR/AFBs, which allows the degradation of Aux/IAA and the release of ARF repression for modulating the expressions of auxin-related genes7. Auxin concentration in the tissues is determined by regulating its biosynthesis, inactivation, and transport. A unique feature of auxin is the polar auxin transport that contributes to most of the directional auxin transport and local auxin concentration. This polar auxin transport is regulated by auxin efflux carriers PIN-FORMED (PIN) family and auxin influx carriers AUX/LAX family proteins. It is considered that auxin is directionally transported across the plasma membrane where PINs localize with a polarity9. ATP-binding cassette ABC transporters of the B class family (ABCB) also play a role in polar auxin transport11. TWISTED DWARF1 (TWD1) has been shown to interact with ABCB protein for auxin transport. ABCB could export auxin independently of PIN proteins, but the functional interaction of ABCB-PIN pairs for auxin transport is also considered. Abbreviations are listed in Table The plant hormone auxin plays an important role in plant gravimorphogenesis. A major endogenous auxin is indole-3-acetic acid (IAA) that regulates various aspects of plant growth and development. In auxin signaling pathway, Aux/IAA proteins inactivate the auxin response factor (ARF) when auxin level is low12. However, the mechanisms of graviperception remain unsolved. The Cholodny–Went theory explains differential growth in tropisms through the redistribution of the plant hormone auxin in elongating organs13. In gravistimulated plants, more auxin accumulates in the lower side than the upper side of shoots and roots in a horizontal position, causing the upward bending of shoots and downward bending of roots. Auxin redistribution following gravistimulation has been verified. Indeed, molecular genetics with many gravitropic mutants has revealed the importance of the roles of auxin transport, redistribution, and response in gravitropism14. In particular, the identification of an auxin efflux carrier PIN-FORMED (PIN) was a significant breakthrough in our understanding of the mechanisms for asymmetric auxin transport and distribution in gravistimulated shoots and roots16. However, unlike some PINs, the pattern of ABCB expression and the phenotypes of ABCB mutants indicate that it is not directly involved in asymmetric redistribution of auxin during gravitropic response11. In roots, for example, PIN3 and PIN7 localize to the plasma membrane of gravisensing columella cells in the root cap. Within 10 min of gravistimulation by reorienting plant seedlings, PIN3 and PIN7 change their location to the new bottom of the plasma membrane, allowing auxin to move to the bottom side of the root cap. Thereafter, PIN2 localizing to the proximal side of the plasma membrane in the lateral root cap and the epidermis, plays a role in the basipetal transportation of auxin from the bottom side of the root cap to the elongation zone. In gravistimulated roots, auxin redistribution is thus established, and transcriptional regulation depending on the auxin level on the upper and lower sides leads to downward bending. Spaceflight experiments with cucumber seedlings in the Space Shuttle and the International Space Station (ISS) showed that the endodermal cells relocalize an auxin efflux carrier, CsPIN1, because of gravistimualtion in space and laterally transport auxin from the upper to lower flank19.Gravisensing apparatuses reside in the endodermal cells of shoots and columella cells of roots, where amyloplast statoliths sediment upon plant reorientation21. The phosphorylation status of PIN proteins, together with GNOM-dependent PIN recycling processes, is hypothesized to participate in polar localization of PIN proteins on the plasma membrane. Dynamics of microfilaments and microtubules (MTs) is an important factor involved in the regulation of trafficking of auxin transporters. It is reported that Sorting Nexin 1 (SNX1) plays a role in PIN2 recycling via interaction with MTs-associated protein CLASP22.Some factors that could be involved in PIN polarization and thereby asymmetric auxin flow have been reported. That is, proteins such as RCN1, PINOID, and D6PK regulate PIN phosphorylation/dephosphorylation24. Interestingly, the alteration of two amino acids in LAZY1 was found to successfully switch negative gravitropism to positive gravitropism in Arabidopsis shoots25. Furthermore, it was revealed that upon amyloplast sedimentation, LAZY1/LAZY1-like proteins get polarized to the plasma membrane of the bottom side of gravisensing cells26. The conserved C terminus in the LAZY1 family (CCL) domains interact with the Brevis radix (BRX) domains of the regulator of chromosome condensation (RCC)-like domains (RLD) proteins, thereby polarly recruiting RLD from the cytoplasm to the plasma membrane26. It was demonstrated that RLD1–4 localize in the root cap and modulate auxin transport through regulation of PIN localization, possibly via a GNOM-like function in PIN trafficking26. This process is required for controlling polarized auxin flow and gravitropic response. Thus, amyloplast position itself may play an important role in gravity sensing/signaling as discussed in next section “Gravity sensor in plants.” However, the mechanism underling the LAZY polarization upon amyloplast sedimentation in gravisensing cells still remains unknown.Recently, it was found that LAZY1 regulates PIN relocalization in gravisensing cells and determines negative gravitropism in shoots and positive gravitropism in rootsArabidopsis lines with GFP reporter gene, pDR5r::GFP, pTAA1::TAA1-GFP, pSCR::SCR–GFP and pARR5::GFP, were used for spaceflight experiments on ISS27. The expressions of the auxin artificial AuxRE promoter construct (pDR5r::GFP), Tryptophan Aminotransferase of Arabidopsis fusion (pTAA1::TAA1-GFP) and Scarecrow fusion (pSCR::SCR–GFP) were used to monitor auxin level, auxin production and auxin-related signals, respectively. There were no differences in the expression patterns and levels of those genes in the primary root tips of seedlings grown under microgravity and 1 G ground conditions. These results implied that auxin gradient in plants is established independently of gravity. On the other hand, spaceflight experiments with pea and maize seedlings showed altered polar auxin transport in microgravity; polar auxin transport in microgravity was decreased in pea epicotyls and accelerated in maize coleoptiles and mesocotyls compared with the 1 G controls29. Recent spaceflight experiments immunohistochemically compared PsPIN1 localization in etiolated pea epicotyls grown under microgravity and 1 G conditions in space30. PsPIN1 proteins were detected in the lower side of the plasma membrane of 80–90% endodermal cells under artificial 1 G conditions, whereas number of those endodermal cells showing polarized PsPIN1 localization significantly decreased in microgravity. The authors consider the change in PsPIN1 localization pattern as a possible cause for the reduction of polar auxin transport in pea epicotyls under microgravity conditions. In maize seedlings, interestingly, the enhanced accumulation of ZmPIN1and the alteration of ZmPIN1a localization in parenchymatous cells of the coleoptiles were likely responsible for the enhanced polar auxin transport in microgravity31. However, species differences of polar auxin transport in microgravity are mysterious.Auxin biosynthesis and distribution in microgravity were also examined by spaceflight experiments in some plant species. Most of those results showed no differences between space- and ground-grown seedlings. Recently, transformed Thus, the PIN-mediated auxin transport and distribution are essential parts of plant gravimorphogenesis. It should be emphasized that some PIN proteins were verified to be gravity responsive in their relocalization on the plasma membrane of the gravisensing cells by spaceflight experiments. Polarization and function of LAZY1/LAZY1-like proteins appear to play a key role in the gravity-induced PIN relocalization and thereby asymmetric auxin flow. To understand the entire regulatory mechanism of plant gravimorphogenesis, it is important to clarify the graviperception mechanism that leads to the regulation of LAZY1/LAZY1-like proteins polarization and PIN relocalization in gravisensing cells.34. Recent live-cell imaging technology has revealed, however, that the movement of the amyloplast is not static but saltatory because its dynamics are dependent on both the gravity vector and intracellular environments such as those of the cytoskeleton and vacuole35. In the shoot statocytes  of Arabidopsis thaliana, the amyloplasts are tightly surrounded by the vacuolar membrane and are supposed to interact with actin filaments36. The abnormal behavior of the vacuolar membrane, however, pushes the amyloplasts to the periphery of the cell in the agravitropic mutant, shoot gravitropism (sgr) 2, which restricts the movement of the amyloplasts and renders them nonsedimentable37. Therefore, inflorescence stems in sgr2 mutants do not sense gravity and do not show a gravitropic response because of nonsedimentable amyloplasts37. distorted1 (dis1)/actin-related protein 3 (arp3) mutants possess irregular thick actin bundles surrounding amyloplasts in their root statocytes (columella cells), and consequently, the amyloplasts do not sediment fully from the actin filaments, resulting in a reduced gravitropic response in roots38. sgr9 mutants also have nonsedimentable, clustered amyloplasts entangled with actin filaments in the endodermal cells because of an excess of interaction between the amyloplasts and the actin filaments and exhibit a weak gravitropic response36. These abnormal phenotypes in both dis1 and sgr9 mutants were compensated by disrupting actin filaments, such as through the use of the actin filament-depolarizing drug latrunculin B38, suggesting that the actin filament is not an essential component for either gravity sensing or gravitropic responses, but rather acts as an intracellular component affecting amyloplast dynamics. Taken together, the dynamics of the vacuolar membrane and actin filaments could diffuse amyloplasts from the bottom of the cell, leading to the nonstatic, saltatory behavior of the plant statolith and amyloplast.As discussed above, plants have a mechanism for gravity sensing using the sedimentation of organelles in order to establish the asymmetric transport of hormones. The most widely accepted model for plant gravity sensing is the starch-statolith hypothesis, in which intracellular sedimentation of the starch-filled organelle (amyloplast) plays a crucial role in the events triggering the initial phases of gravity sensing in plantsvia actin, resulting in intracellular ionic signaling41. Changes in the gravity vector (inclining the specimens) elevate cytosolic calcium concentrations in Arabidopsis seedlings43. This Ca2+ response is attenuated with latrunculin B and mechanosensitive ion channel blockers such as Gd3+ 42, supporting a model involving actin filaments that function as a tether to activate mechanosensitive channels39. Actin filaments may have both a positive role in the activation of mechanosensitive channels upon gravity stimulation and a negative role in the sedimentary dynamics of amyloplasts as discussed above. To demonstrate this, direct observations of Ca2+ responses in both the shoot endodermal and root columella cells are needed. An alternative model is the position-sensing hypothesis in which the spatial distribution of amyloplasts upon gravity stimulation is detected as a signal for gravity sensing44. In this hypothesis, a putative machinery, rather than mechanosensitive channels sensing the gravitational force exerted on the amyloplasts, detects the position (state) of the amyloplasts in gravity sensing cells, consistent with data indicating that gravitropic responses in wheat coleoptile are dependent on the angle of inclination of the specimens but not on the amplitude of the gravitational force45. These data suggest a variety of gravity sensing mechanisms in diverse plant species such as monocots or dicots which are, however, quite different from those of animals.A long-lasting question regarding gravity sensing in plants is how the physical process of amyloplast sedimentation is converted into intracellular signals. The most reasonable models, such as the inner ear (hair cell) system of vertebrates, suggest that amyloplast sedimentation activates mechanosensitive ion channels 2+ response, which has been reported in many plant species46. Thus, it is plausible that mechanosensitive channels are the primary sensors of plant graviperception evoking the Ca2+ response.As discussed above, gravity is the force that generates several effects such as the weight leading to the sedimentation of amyloplast statoliths, deformation and compression of the cells, and fluid shift in vasculature, all of which generate mechanical stresses in plasma and endomembranes. One of the earliest response to changes in gravity vector and magnitude is the CaE. coli47. Among the 10 members of the MSL protein in Arabidopsis, MSL1 localizes to the inner mitochondrial membrane, whereas MSL2 and 3 are found at the inner plastid membrane, and MSL8, 9, and 10 localize to the plasma membrane48. MSL2 and 3 regulate the size and shape of the plastid, and MSL8 is required for the rehydration of the pollen grain, indicating that a major role of MSL proteins is osmotic regulation. Yeast two-hybrid assays demonstrated that MSL2 and 3 interact with each other, suggesting that some MSLs can form heteromeric channels49. MCA proteins have been identified as complements of the mid1 mutant of the yeast that is defective in Ca2+ influx50. MCA1 and MCA2 localize in the plasma membrane and mediate the cold-induced Ca2+ response that leads to cold tolerance according to the CBF/DREB1-independent pathway51. MCA1, but not MCA2, is required for the penetration of roots into harder agar and results in the retardation of the leafing and bolting of the mutant. The expression levels of MCA1 and MCA2 were increased under hypergravity conditions in the absence of light, and the hypocotyl elongation under these conditions was attenuated in the overexpressing seedlings. Therefore, MCA proteins might be responsible for resistance to gravity52. OSCA proteins, homologous to the TMEM63 family of proteins known throughout eukaryotes, have been identified from Arabidopsis mutants exhibiting a low hyperosmolality-induced Ca2+ response53. An ortholog of animal Piezo protein, the mechanosensitive cation channel for touch sensation and vascular development, is commonly conserved in monocots and suppresses the systemic movement of viruses54.MSL proteins share the C-terminal transmembrane (TM) segment corresponding to the pore-forming transmembrane segment of MscS  in Xenopus oocytes and HEK cells56. Electrophysiological studies using Arabidopsis mutants and Xenopus oocytes have revealed that MSL proteins show a preference for anions over cations, leading to depolarization of the plasma membrane and the following Ca2+ response through the activation of voltage-dependent cation channels57. Most recently, a lack of rapidly activated mechanosensitive Ca2+-permeable channel activity (RMA) was reported in Arabidopsis DEK1 mutants58. Although there is no sequence homology, AtDEK1 has a high number of transmembrane helices as with mammalian Piezo proteins, and RMA shows low conductance and rapid inactivation. These electrophysiological studies have demonstrated that the thresholds of membrane stretch for the activation, conductance, and inactivation time constant of plant mechanosensitive channels are varied, even within the same family.Mechanosensitive cation channel activity in MCAs and OSCAs has been recorded using patch-clamp techniques with heterologous expression in 47. Interestingly, most mechanosensitive channels are expressed in the vasculature, where gravity-induced Ca2+ response is observed46. In root statocytes of Brassica grown in ISS, ten-minute onset (µg to 1 g) or removal (1 g to µg) of a gravity-induced Ca2+ response in absence of a significant statolith displacement59. Changes in gravity vector and magnitude promote a Ca2+ response with similar kinetics46. It suggests that multiple mechanosensitive channels in plasma- and endomembranes could be differentially activated by gravity, and promotes a small Ca2+ response that is amplified by common intracellular machineries. Thus, pharmacological studies suggest that gravity-induced Ca2+ response is greatly amplified by Ca2+-induced Ca2+-release (CICR) from organelles through signaling cascades, including PLC activation43. Subcellular and tissue-specific distributions of gravity-induced Ca2+ response and the underlying molecular mechanisms should be investigated more deeply in order to understand graviperception mechanisms in plants.Although series of proteins and their physiological roles have been characterized in numerous aspects, the mechanosensitive channels responsible for gravitropism have not yet been identified. Overlapping tissue expression patterns suggest that mechanosensitive channels in the same tissue share physiological functions. Thus, most mutants, even those that lacking five MSLs , do not show a significant phenotype60. This demonstration that YAP is required for withstanding gravity in generating a 3D body/organ shape first suggested that YAP not only transduces gravity responses as a mechano-transducer61, but more strikingly acts as a mechano-effector for withstanding gravity, forming a mechanical negative-feedback60. Since YAP is the key regulator orchestrating organ growth62, this review will focus on the role of YAP in linking gravity response with organ growth and maintenance.Although plants and animals share common mechanisms for gravity sensing, such as the homologous mechanosensitive ion channels discussed above, the transcriptional coactivator Yes-associated protein (YAP) is a mechanosensitive machinery specific to animals. The relationship between gravity and YAP was first revealed by the analysis of the medaka fish YAP mutant. The body of this mutant was flattened because of its inability to withstand gravity64. YAP nuclear localization is controlled mainly by the Hippo pathway and F-actin-mediated signaling responses to diverse signals, e.g., growth factors and mechanical stimuli65. YAP is able to expand the organ size when constitutively activated62 and is involved in such diseases as cancer and fibrosis65.YAP and its paralog TAZ  act as transcriptional co-activators, mainly in the nucleus66 and its target gene ARHGAP18 and then negatively regulates F-actin polymerization, suppressing YAP activity60 , an osteoclast differentiation factor, and as a negative regulator of osteoblast differentiation by sclerostin (Sost)71. Importantly, expressions of these genes vary in response to mechanical loading or unloading to osteocytes in the bone. Osteocyte cell body and dendrites reside in the lacunae and canaliculi, respectively, and mechanical loading induces minute changes in the structure of the bone that generate interstitial fluid flow in the lacuno-canalicular system. This flow acts as a mechanical loading, similar as pressure and shear stress, and affects osteocytes directly72.Osteocytes, another type of bone cell, are differentiated from osteoblasts and embedded in the bone matrix have many dendrites formed through osteocytogenesis that communicate either with each other or with the osteoblasts and osteoclasts at the bone surface73. In addition, the cytosolic signaling adapter protein p130Cas, a cellular mechanosensing molecule74, is involved in the regulation of bone homeostasis in response to mechanical loading in osteocytes75. Interestingly, p130Cas translocates into the nucleus and negatively regulates NF-κB activity to suppress bone resorption by downregulating the expression of RANKL. These findings suggest that the p130Cas- NF-κB axis in osteocytes is a potential target for treatment against disuse osteoporosis.Such mechanical loadings to osteocytes as described above can activate mechanotransduction mediators such as ion channels, connexins, integrins, and cytoskeleton-related moleculesAlthough the critical significance of mechanical loading to the bone has been clearly elucidated, a large portion of the molecular mechanisms underlying the mechanical regulation of bone homeostasis is not understood. Efforts to clarify these mechanisms will be a promising strategy to prevent bone loss during future space missions.76. It is thought to be triggered by enhanced osteoclast-mediated bone resorption at the endocortical surface and suppressed bone-forming activity in the periosteum. The periosteum, the highly vascularized outer membrane that covers all bones except for joints, generates the cortical bone in physiological and pathological situations through the provision of osteoblasts77. The periosteum contains two layers: an outer layer of fibroblasts and an inner layer composed of bone-forming osteoblasts. Although the periosteum is not highly sensitive to mechanical loading compared to the endocortical surface, it nonetheless responds to loading and gives rise to bones in a variety of animal models. The unloading model of the hind limb reduces bone formation in the cortical bone as well as in the trabecular bone78. Conversely, periosteal bone formation is stimulated by enhanced loading using in vivo models of axial loading and three-point bending80. The alteration of gene expression patterns and cell morphologies within the periosteum after loading provides evidence that periosteal cells sense loading stimuli81.The deterioration of the bone microarchitecture during spaceflight occurs not only in the trabecular bone but also in the cortical bone82. A recent study has revealed that Cathepsin K (CTSK)-lineage populations within the periosteum contain postnatal self-renewing and multipotent stem cells83. The deletion of Osterix, encoded by the Sp7 gene, in CTSK-lineage cells results in impaired bone formation and fracture healing83. Furthermore, Prx1-lineage mesenchymal cells that contain SSC sense loading stimuli through their primary cilia indicate loading-dependent bone formation82. More recently, Nestin+ and Leptin+ cells have been shown to generate osteoblasts for periosteal bone formation84. On the other hand, some studies have shown that loading alters gene expression patterns, including extracellular molecules in osteoblasts85. Thus, the osteoblast may function as a mechanotransducer that induces osteogenic differentiation of SSCs in the periosteum. Accordingly, direct or indirect loading can activate several types of SSC to induce cortical bone formation.Among the cells responsible for sensing physical loading is skeletal stem cell (SSC) because loading-induced bone formation requires activation of the periosteal SSC to give rise to osteoblasts. The periosteal SSC displays a unique gene expression pattern and exhibits high regenerative capacity in response to bone injury when compared to bone marrow skeletal stem cells (BMSC)86. Unloading-induced muscle wasting is mediated by a decrease of protein synthesis in the homeostasis of muscle cells and an increase of catabolism. Consequently, there must be a molecule that senses and transduces the signals originating from mechanical loading. One of the candidates for such a load transducer is a nonselective cation channel, the canonical transient receptor potential channel (TRPC). Members of the TRPC channels, namely, TRPC1, TRPC3, and TRPC6, are reportedly activated downstream of mechanical signals in addition to phospholipase C-coupled cell surface receptor activation87. TRPC channels play important roles in the activation of protein phosphatase calcineurin (CaN). CaN regulates the Ca2+-dependent transcription factor, the nuclear factor of activated T cells (NFAT), and the peroxisome proliferator-activated receptor γ88. Both proteins are important for myogenesis. Exposure of C2C12 skeletal myoblasts to microgravity induces the reduction of TRPC1 expression, which arrests the cell cycle at the G2/M phase, thereby inhibiting myoblast proliferation89. The importance of TRPC1 has also been demonstrated in muscle regrowth after unloading-induced atrophy. Hind limb unloading induces the reduction of TRPC1 expression, which persists even after reloading90. The expression of the TRPC3 channel is also suppressed at complete atrophy and in the early recovered phase90. These changes in the expression of the TRPC1 and TRPC3 channels are consistent with the muscle mass, suggesting that these channels play important roles in load-dependent muscle growth.Muscle atrophy is another major health problem in life in space and involves the decrease of muscle mass in response to the reduction of hemodynamic loads. It is known to be caused by microgravity, long term bed rest, and cancer cachexia91. ROS are produced as a byproduct of the mitochondrial respiratory chain or are produced enzymatically by NADPH oxidases (NOX) within the cell. In cardiac muscles, ROS production by the NOX2 protein is physiologically important for Ca2+ homeostasis and is activated mechanically during diastole92. However, in pathological conditions, NOX2-mediated ROS production causes cardiac remodeling in response to various stresses. It has also been noted that pathological situations in muscle tissue can engender abnormal Ca2+ signaling. Since some NOX isoforms require Ca2+ for activation, it is plausible that there exists a crosstalk between pathological NOX activation and abnormal Ca2+ signaling. TRPC3 and NOX2 proteins exist at this crossroads of signaling pathways. Additionally, it has been demonstrated that the TRPC3 channels play an important role in NOX2 protein stabilization by protecting them from proteasomal degradation93. ROS production mediated by TRPC3 and NOX2 coupling causes cardiac muscle atrophy in stressed hearts, in which the hemodynamic load is reduced95. Therefore, TRPC channels might have dual roles in unloading-induced muscle atrophy: the first is the regulation of myoblast proliferation via CaN activation, and the second is the production of ROS, which induces catabolic remodeling of muscle tissue.It is widely accepted that oxidative stresses caused by the aberrant production of reactive oxygen species (ROS) or reactive nitrogen species are key regulators for catabolic muscle wasting96. MSC self-renewal and differentiation are known to be controlled by a diverse set of soluble factors, including growth factors or cytokines. In addition, the fate of MSCs has been shown to be influenced by mechanical stresses or surrounding physical microenvironments, such as substrate stiffness97, or changes in gravity. Many space experiments and ground-based studies have demonstrated that MSCs are very sensitive to the modulation of gravitational stimuli and exhibit various responses against such effects98. The exposure of MSCs to microgravity or simulated microgravity induces characteristic physiological responses, including remodeling of the cytoskeleton and the disruption of the stress fiber100, reduced activity in transcriptional coactivator YAP/TAZ68, suppression of osteoblastic differentiation, and the promotion of adipogenesis102, some of which were also observed in other nonspecialized animal cells.Mesenchymal stem cells (MSCs) are crucial in the field of regenerative medicine by virtue of their self-renewal and multi-differentiation potentials103. In the early phase (30 min to 6 h) of exposure to microgravity, environmental changes experienced by the cytoskeleton have been observed, including a reduced amount or thinning of stress fibers103 , and actin fibers have been established to function as mechanosensors for various types of cells. It has been postulated that MSCs also utilize these common sensors to detect changes in gravity, since MSCs have no specific gravity sensors, as is the case for organs such as the animal gravity sensor statocyst. Recent studies have proposed that the cytoskeleton may function as an initial sensor for microgravity104. For example, our fluorescent, ubiquitination-based cell cycle indicator (Fucci) technology harnesses the cell-cycle-dependent proteolysis of Cdt1 and Geminin fused to fluorescent proteins of different colors106. Although considerable progress has been made toward understanding the mechanisms of cell cycle progression on Earth107, much less is known about how cell proliferation is affected by microgravity in outer space, where humans will live in the future.Regulation of the cell cycle is crucial for the maintenance of organs, such as bones and muscles. Technological innovation in bio-imaging has recently used fluorescent proteins, and we advocate real-time, single-cell imaging techniques to accurately and comprehensively dissect molecular and cellular principles and explain natural and sample-originated heterogeneity in biology108, but remains controversial. Because individual studies use different experimental setups and different types of cells, discrepancies in results might arise inevitably. The 3D-clinorotation system provides time-averaged simulated microgravity as an alternative to real microgravity conditions109, and the effects of microgravity on living cells have been studied using this device. For example, cultured cells were exposed to microgravity for several days. Cells were seeded in 25 cm2 flasks or on a DCC (disposable cell culture) plate110, which were then fully filled with a CO2-equilibrated medium and accommodated on the 3D-clinorotation device. After exposure, the number of cells was quantified to determine whether microgravity inhibits the proliferation of cells.As discussed above, regulation of the cell cycle is crucial for growth and maintenance of organs. To directly understand the precise molecular mechanisms of how individual cells in organs respond to microgravity, several simulated microgravity experiments have been performed on the ground using cultured cells. The relationship between gravity force and cell cycle progression has been reviewed110) plate for fluorescence observation. This system can be used in the cell biology experiment facility of the ISS. We have already generated a variety of human cell lines that constitutively express Fucci probes. Hopefully, this will enable us to better understand how cells behave in outer space.To visualize the progression of the cell cycle of cultured cells in real time at the single-cell level during exposure to microgravity, we are currently developing a 3D-clinorotation 2D-microscopy system. The system accommodates a portable fluorescence microscope that we invented on the basis of a smartphone and a DCC-G (glass-based DCCResponse to gravity is a cellular process of mechanotransduction in both plants and animals. Interestingly, although plants and animals seem to be very genetically distant, they share common mechanisms for gravity sensing, e.g., an actin cytoskeleton and mechanosensitive ion channels combined to this skeleton. On the other hand, animals evolved unique systems for gravisensing as exemplified by the transcriptional coactivator YAP/TAZ, which affects the cell fate of bones, muscles, and stem cells. Knowledge derived from extensive studies of gravisensing will contribute to medicine on Earth, e.g., understanding osteoporosis, muscle atrophy, and cancer biology. However, in the present age of preparation for human space exploration and colonization, or example through the Moon base and Mars exploration, understanding cellular responses to gravity will form the foundations of living in space.


Here, we will review the known cellular and molecular interactions occurring between monoclonal B lymphocytes and their tissue microenvironment and the current literature describing innovative in vitro models developed in particular to study chronic lymphocytic leukemia (CLL). We will also elaborate on the possibility to further improve such systems based on the current knowledge of the key molecules/signals present in the microenvironment. In particular, we think that future models should be developed as 3D culture systems with a higher level of cellular and molecular complexity, to replicate microenvironmental-induced signaling. We believe that innovative 3D-models may therefore improve the knowledge on pathogenic mechanisms leading to the dissemination and homing of leukemia cells and consequently the identification of therapeutic targets.Over the last decade, the active role of the microenvironment in the pathogenesis, development and drug resistance of B cell malignancies has been clearly established. It is known that the tissue microenvironment promotes proliferation and drug resistance of leukemic cells suggesting that successful treatments of B cell malignancies must target the leukemic cells within these compartments. However, the cross-talk occurring between cancer cells and the tissue microenvironment still needs to be fully elucidated. In solid tumors, this lack of knowledge has led to the development of new and more complex  In recent decades, novel experimental strategies have allowed for great advancements in cancer research providing major insights into the complexity of tumor development , 2. Partin vitro systems and animal models  structure of human tissues, whereby cell-cell and cell-extracellular matrix (ECM) interactions occur creating the so-called microenvironment. Not only the microenvironmental interactions but also the 3D structure itself are considered key for cell proliferation, differentiation and mobility, as they occur in the context of cancer development  cell cultures l models . Althougelopment . In addil models . 3D cultl models . In partl models . These 3 outcome .in vitro 3D models mimicking specialized microenvironments of lymphoid tissues and incorporating advanced biomaterials and microfluidics, helped identify novel cellular, biochemical, and biophysical interactions and elucidate new regulatory mechanisms and potential therapeutic targets that could not otherwise have been studied in conventional 2D cultures . Signals occurring in tissue compartments (Bone Marrow - BM) and secondary lymphoid organs are pivotal for survival, proliferation, homing and trafficking of the malignant cells . CalissaLL cells . These sLL cells . In tissLL cells . In partLL cells . One hasLL cells  thus sugo models .in vivo and the cell heterogeneity present in the leukemic microenvironment pose a number of challenges when trying to dissect the specific role of each component in the development of CLL. Based on this, it becomes obvious that traditional preclinical in vitro modeling using only primary CLL cells or even cell lines have become obsolete. This is clearly evident by the fact that CLL cells undergo spontaneous apoptosis when cultured in vitro unless substitutes of survival signals found in the tumor microenvironment are provided , which are crucial for the well-being of normal haematopoietic cells, also regulate the survival of malignant cells in the bone marrow. The interaction between VCAM-1 on the BMSCs and VLA-4 integrin on CLL cells leads to the upregulation of the anti-apoptotic molecule MCL1. In addition, BMSCs, similarly to NLCs, secrete CXCL12 that interacts with CXCR4 on CLL cells, promoting tissue homing and regulating cell trafficking (Nurse-like cells (NLCs) are found in secondary lymphoid organs where they activate the BCR signaling in CLL cells and secrete CXCL12 and CXCL13 that attract CLL cells into the tissue microenvironment. They also express BAFF and APRIL that promote survival and proliferation of CLL cells, thus providing full support for the leukemic cells as seen fficking , 20. Keefficking . In partfficking .+ T cells also promote CLL survival in lymphoid tissues  in general can protect different types of leukemia from spontaneous and chemotherapy-induced apoptosis .in vitro with FDCs were protected from spontaneous apoptosis as a result of the ligation of CD44 on CLL cells and up-regulation of MCL1, a member of the BCL2 family of anti-apoptotic proteins . Stromal co-culture systems were first described by Panayiotidis et al. in 1996. They showed that culturing CLL cells in contact with BMSCs could increase the percentage of viable cells after 10 days of culture by more than 30% compared to controls. Similarly, CLL cells incubated proteins . Later, al cells . In otheal cells .ex vivo short-term culture system to potentially predict the clinical response to therapeutics including novel inhibitors (in particular PI3Kδ and BTK inhibitors) by quantifying not only the pro-apoptotic effect of conventional drugs but also the anti-proliferative effect that are characteristically exerted by kinase inhibitors. After a thorough evaluation, alone and in combination, of several cell-extrinsic factors known to affect survival and growth of CLL cells, the authors proposed an optimized co-culture setting with sustained viability and proliferation of CLL cells, resembling what may occur within the infiltrate tissues in vivo. The combination includes: a cellular adherent component , soluble factors such as CpG + IL2 and the addition of human serum, CLL plasma and erythrocyte fraction.As an evolution of the cell- or molecule-based approaches, more complex co-culture methods have recently been developed, however still in a 2D setting. Primo et al.  developeper se limited in the possibility to fully reproduce the situation and the events occurring in vivo due to the intrinsic limitations of a flat, 2D culture.However, all these systems are in vitro tissue models with a 3D structure resembling in vivo tumor growth was more obvious, this need was perceived much later in hematological cancers, in particular CLL, due to the circulating nature of the disease. It is now evident that the circulating cells do not represent the actual reservoir of the disease, that is composed by the cells accumulating in solid tissues, in particular in the proliferation centers within LN or the BM  components  thereby more closely resembling the actual tumor microenvironment (“biomimicry of the tissue of origin”). Examples of this model include Matrigel and Collagens or decellularized tissues or organs. However, natural products have innate differences during the commercial production process leading to heterogeneity in their composition between different lots, also based on the tissues of origin, thus impeding full potential reproducibility of the experimental settings.On the other hand, synthetic or animal-free polymers scaffolds are made of biologically compatible polymers and hydrogels , 36 thatin vivo response to therapy.Both scaffold types have been used to recreate lymphoid tissues. The BM microenvironment niche has been the most investigated for acute myeloid leukemia (AML) and multiple myeloma (MM) to study the resistance to chemotherapeutics. Aljitawi et al. designed a 3D BM-microenvironment by co-culturing AML cell lines with human bone marrow derived mesenchymal cells in a synthetic scaffold and demonstrated significant differences in leukemic cell response to chemotherapy. In particular, leukemic cells cultured in 3D were more resistant to drug-induced apoptosis compared to cells cultured in 2D . De la Pin vitro 3D cellular clusters directly derived from primary tissues, embryonic stem cells, or induced pluripotent stem cells grown on artificial ECM . Organoids exhibit similar organ functionality as the tissue of origin, and they are widely utilized for solid tumors and drug screening  spinner-flask bioreactors: used for the seeding of cells into 3D scaffolds and for subsequent culture of the constructs; 2) Rotating-wall vessels (RWV) bioreactors: it provides a dynamic laminar flow generated by a rotating fluid environment and it reduces diffusional limitations of nutrients and wastes, while producing low levels of shear flow; 3) direct perfusion bioreactors: here the culture medium is perfused directly through the pores of the cell-seeded 3D scaffold. During seeding, cells are transported directly into the scaffold pores, resulting in a uniform cell distribution , allowing the development of functional myeloma-stroma interactions and MM cell long-term survival and a more precise determination of the impact of the proteasome-inhibitor bortezomib on MM cells and on the microenvironment to predict actual responses. We recently adapted this model to study the interactions that CLL cells may engage with the BM tissue microenvironment , project code (MIS) 5041673 (to PG).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.The reviewer YH declared a past co-authorship with one of the authors PG to the handling editor.


The term aggressive variant prostate cancer (AVPCa) refers to androgen receptor (AR)-independent anaplastic forms of prostate cancer (PCa), clinically characterized by a rapidly progressive disease course. This involves hormone refractoriness and metastasis in visceral sites. Morphologically, AVPCa is made up of solid sheets of cells devoid of pleomorphism, with round and enlarged nuclei with prominent nucleoli and slightly basophilic cytoplasm. The cells do not show the typical architectural features of prostatic adenocarcinoma and mimic the undifferentiated carcinoma of other organs and locations. The final diagnosis is based on the immunohistochemical expression of markers usually seen in the prostate, such as prostate-specific membrane antigen (PSMA). A subset of AVPCa can also express neuroendocrine (NE) markers such as chromogranin A, synaptophysin and CD56. This letter subset represents an intermediate part of the spectrum of NE tumors which ranges from small cell to large cell carcinoma. All such tumors can develop following potent androgen receptor pathway inhibition. This means that castration-resistant prostate cancer (CRPCa) transdifferentiates and becomes a treatment-related NE PCa in a clonally divergent manner. The tumors that do not show NE differentiation might harbor somatic and/or germline alterations in the DNA repair pathway. The identification of these subtypes has direct clinical relevance with regard to the potential benefit of platinum-based chemotherapy, poly (ADP-ribose) polymerase inhibitors and likely further therapies. Men with CRPCa may evolve an androgen receptor (AR)-independent phenotype, characterized by a rapidly progressive disease course ,2,3. ThiIt is outside the scope of this contribution to deal with metastatic hormone-sensitive PCa, a tumor that can show clinical, morphological and molecular features of aggressiveness.The terminology of the aggressive variant of CRPC lacks consensus among experts.These aggressive tumors have been called “Anaplastic Prostate Cancer” and “Anaplastic Prostate Carcinoma” (APCa) ,3,4,5,6.The term “Neuroendocrine prostate cancer” (NEPCa) has also been used to refer to this group of tumors . This teThe term “Intermediate Atypical Prostate Cancer” (IAPCa) has also been used to refer to CRPCa in men who develop mixed pathologic and molecular features overlapping with NEPCa ,7. Howev“Histologic evidence of small-cell NEPCa (pure or mixed);The presence of exclusively visceral metastases;Radiographically predominant lytic bone metastases by plain x-ray or CT scan;Bulky (≥5 cm) lymphadenopathy or bulky (≥5 cm) high-grade (Gleason ≥ 8)  tumor mass in prostate/pelvis;Low PSA (≤10 ng/mL) at initial presentation (prior to ADT or at symptomatic progression in the castrate setting) plus high volume (≥20) bone metastases;elevated serum LDH (≥2 × ULN), malignant hypercalcemia,elevated serum CEA (≥2 × ULN);Presence of neuroendocrine markers on histology (positive staining of chromogranin A or synaptophysin) or in serum ) at initial diagnosis or at progression, plus any of the following in the absence of other causes:Short interval (≤ 6 months) to androgen-independent progression following the initiation of hormonal therapy with or without the presence of neuroendocrine markers” ,8.“Aggressive variant prostate cancer” (AVPCa)  is the pIt worth mentioning the updated prognostic model by Halabi et al.  for predBased on the morphologic appearance, and without knowing the previous history of the patients, such tumors in the bladder wall could have been considered as high grade invasive urothelial carcinoma because of their similarity to such tumors B. HoweveAVPCa is associated with a high frequency of distant metastasis in a typical site  and/or in atypical sites, such as liver, brain, lung, pleura, mediastinum, peritoneum and adrenal . Figure The three cases presented above, all with a previous history of potent androgen receptor pathway inhibition, exemplify the basic morphology of AVPCa. None of them bears resemblance to typical cases of prostatic adenocarcinoma with acinar or ductal features. There are no attempts to form lumina D. They aIn such tumors, the final diagnosis depends on the application of immunohistochemical markers that point to the diagnosis of prostate origin, in particular PSMA , and the exclusion of malignancies from other sites, including the bladder, such as the presence of GATA3 B, insertA first question is whether it is possible to distinguish AVPCas with NE differentiation from those without on the basis of the pure morphology, that is, the hematoxylin-eosin-stained sections. The answer is no, because the neoplastic population is quite homogenous in morphology and there is no cellular hint to the presence of NE differentiation, even in cases in which the tumor is composed of cells co-expressing NE and prostate markers. This means that immunohistochemistry has to be performed in all cases of AVPCa to detect an NE differentiation. This is in agreement with the results of the investigation by Labrecque et al , showingAn additional question is whether the morphologic spectrum of NE differentiation in AVPCa can be considered to be much wider. The answer is that the type of tumor described above could represent the intermediate part of a morphologic spectrum of NE tumors, a spectrum that could range from small cells to large cells ,5,13 se. This meA further question is whether NE differentiation can be observed in PCas that are still hormone sensitive and therefore not really part of the spectrum of AVPCa. The answer is “yes”, and they have the morphology of mixed acinar and NE adenocarcinoma  . It is an increasingly common phenomenon as a treatment-emergent adaptive response under androgen signaling inhibition ,22,23. TSmCC represents between 1% and 5% of all prostatic malignancies when mixed adenocarcinoma-neuroendocrine carcinoma are included ,24. ManyThere are conflicting data as to whether SmCC originating in the prostate is positive for TTF-1, a marker that is usually expressed in SmCC of the lung. A recent study demonstrated that the stain for TTF-1 is positive in approximately 50% of cases in the prostate ,25. The CD44 is a cell-surface molecule that can identify cancer stem/progenitor cells in PCa. Strong and diffuse membrane staining for this marker is seen in 100% of prostatic SmCCs   in PCa has shown that the greatest proportion of cells with strong stainings is seen in SSTR2, mainly in the group of CRPCa with NE differentiation . The cloEmerging clinically relevant subcategories in AVPCa include disease that demonstrates not only NE differentiation but also tumors with somatic and/or germline alterations in the DNA repair pathway . “IdentiA recent study by Aparicio et al. dealt with AVPCa, defined by them as “a clinically defined subset of the disease that shares virulent and atypical clinical features and chemotherapy sensitivity with the small cell prostate carcinomas” (SmCC) . They obAurora kinase A (AURKA) amplification and overexpression are implicated in the pathogenesis of SmCC . A high Sequencing DNA for somatic mutations requires PCa material—in particular, biopsies—surgical material and circulating tumor cells or circulating tumor DNA in the blood . SomaticAdvances in the technology of DNA sequencing have clarified the genomic landscape of PCa, including AVPCa. Tumors possessing DNA repair mutations and mutations of the defective DNA repair pathway are quite common in advanced stages of neoplasia, thus showing a poor prognosis related to these mutations. Between 20%–25% of men with mCRPCa can present mutations in the DNA repair pathway (such as BRCA genes) . The knoA defective DNA repair system can increase the frequency of mutations in the DNA. This is considered a very important element in the development of the antitumor immune response. Mutations in the BRCA2 gene have been observed in melanoma patients with a better response to anti-PD-1 therapy . Such fiA recent study by Rantapero et al. has investigated the inherited DNA repair gene mutations in men with lethal PCa in Finnish and Swedish populations . The autGermline mutations in the mismatch repair (MMR) genes  are seen in Lynch syndrome, an inherited condition that predisposes individuals to an increased risk of developing many different types of cancers. Studies have suggested a slight increase in risk for PCa in men with this syndrome ,49. HOXBSequencing DNA for somatic mutations can also be done in circulating tumor cells or circulating tumor DNA in the blood . There aEvidence from several cancers suggests that an increased aggressiveness is associated with the up-regulation of signaling pathways and with the acquisition of properties seen in stem cells ,16. SmitAVPCa refers to AR-independent anaplastic forms of PCa characterized clinically by a rapidly progressive disease course . BiopsieRecent investigations have shown that tissue biopsies from patients with AVPCa can provide molecular information that is clinically relevant, including somatic mutations to the DNA damage repair pathway, mutations other than defective DNA repair mechanisms  and the The morphologic spectrum of treatment-related aggressive variants of PCa also includes rare histological variants such as carcinosarcoma C, adenos


This review offers an update on research conducted with FinnTwin12 (FT12), the youngest of the three Finnish Twin Cohorts. FT12 was designed as a two-stage study. In the first stage, we conducted multiwave questionnaire research enrolling all eligible twins born in Finland during 1983–1987 along with their biological parents. In stage 2, we intensively studied a subset of these twins with in-school assessments at age 12 and semistructured poly-diagnostic interviews at age 14. At baseline, parents of intensively studied twins were administered the adult version of the interview. Laboratory studies with repeat interviews, neuropsychological tests, and collection of DNA were made of intensively studied twins during follow-up in early adulthood. The basic aim of the FT12 study design was to obtain information on individual, familial and school/neighborhood risks for substance use/abuse prior to the onset of regular tobacco and alcohol use and then track trajectories of use and abuse and their consequences into adulthood. But the longitudinal assessments were not narrowly limited to this basic aim, and with multiwave, multirater assessments from ages 11 to 12, the study has created a richly informative data set for analyses of gene–environment interactions of both candidate genes and genomewide measures with measured risk-relevant environments. Because 25 years have elapsed since the start of the study, we are planning a fifth-wave follow-up assessment. As with the Older Finnish Twin Cohort and the FinnTwin16 Cohort both reviewed this year in Twin Research and Human Genetics, FinnTwin12 (FT12), most recently reviewed in Subsequent waves of follow-up in FT12 have created a rich dataset of behavioral assessments from multiple sources across three stages of adolescence and into early adulthood. Results permit identification of risk factors predictive of alcohol use, tracking the trajectories of use across adolescence and subsequent development of alcohol-related problems in early adulthood. FT12 has assessed broad developmental aspects of the twins’ lives from preadolescence, through late adolescence and into young adulthood, with assessments of family environment, relationships with cotwin, with parents and with peers, adding measures of school, neighborhood and community environments, and information on health behaviors, pubertal maturation and lifestyle factors. Intensive study of a subset of the FT12 sample begun during the winter–spring of the year in which twins reached age 12, included peer nominations and in-school questionnaire assessments of twins, and a gender-and age-matched, unrelated nontwin classmate control.Parents of intensively studied twins were interviewed at baseline with the Semi-Structured Assessment for Genetics of Alcohol SSAGA; , and wheMuch of the research in FT12 has been guided by a developmental perspective of alcoholism and a multilevel approach to understanding behavioral, emotional and physical health. The diathesis–stress model , illustrTwins enrolled into FT12 were born 1983 through 1987; they were identified through Finland’s Central Population Registry (CPR). Ascertainment was exhaustive, and twins in all pairs with both twins alive, resident in Finland and enrolled in normal public schools, were invited to participate. To date, four waves of questionnaire data have been collected from FT12 participants. Key information regarding the participation of the twins and parents in the epidemiological, questionnaire-based study waves is provided in A total of 2705 families  returned the initial family questionnaire mailed late in the year in which successive twin birth cohorts reached age 11. The family questionnaire was mailed to all families of all eligible twins, using updated residential postal addresses obtained from the Population Registry. Return of the completed family questionnaire gave us permission to contact the twin children, and questionnaires for twin boys and girls, and those for their parents, were then mailed. Parents living apart from their twins were included in these postal mailouts. Parent and teacher ratings of all twins were collected at baseline, with high participation rates; 92% of the parents and 93% of the twins’ classroom teachers returned ratings. Cooperation at these initial stages was not associated with family structure, area of residence within Finland, parental age, or sex or zygosity of twin-pairs. All twins in the FT12 sample were invited to participate in the first follow-up survey at age 14 (with 92% retention). Questionnaires for the second follow-up at age 17 (75% retention) were sent only to those who responded earlier, but in young adulthood , questionnaires were again sent to all (the now adult twins) to permit them to withdraw from further study if they chose to do so.n = 1854), for whom we have collected much more detailed phenotypic and genetic information. In creating the invited subsample (1035 families), random sampling preceded selective enrichment for familial alcoholism risk. A random sample (of predetermined n) was selected from each birth cohort; to that random sample, all remaining twins in that cohort for whom one or both parents exceeded the threshold on a questionnaire screen for alcoholism  years: adult SSAGA interviews in person or via telephone if a twin could not travel to Helsinki. The in-person testing also included neuropsychological assessments and collection of DNA and serum samples. In total, 73% completed young adult SSAGAs and 1260 individuals provided DNA [526 of whom were monozygotic (MZ) twins]; 812 also completed a laboratory assessment that included a test battery assessing neurocognitive functioning.In young adulthood, the intensive sample of twins was invited to in-person testing in Helsinki. This wave 4 data collection in 2006–2009 was the most comprehensive assessment of the twins conducted to date. It included structured psychiatric interviews at an average age of 21.9  based on questionnaires and interviews for comorbid DSM-IV diagnoses , while all twins in the full epidemiological sample were asked about their alcohol and tobacco use in questionnaires.At age 12, teachers, parents and twins in the full FT12 sample reported on twins’ emotional problems, behavioral problems and social adjustment using the Multidimensional Peer Nomination Inventory (MPNI) and teacher ratings  were obtained again on the full sample at age 14. Peer nominations were obtained at age 12 for the intensive sample with the MPNI in parallel teacher, parent and peer format . For morIn the age 17 follow-up questionnaire, twins completed the Karolinska Scale of Personality , with scIn adolescence, twins reported on their recent life events , their pAt all ages, participants reported on their self-rated overall health and 10 somatic symptoms  and DNA methylation using the 450-k Illumina array. A nuclear magnetic resonance (NMR)-based metabolomics panel was used . We haveWe update vital status from the CPR as needed, and What follows is an overview of major areas of scientific knowledge to which FT12 data analyses have contributed.FT12, in combination with FinnTwin16, has been pivotal in advancing our understanding of how genetic and environmental influences contribute to alcohol use and related behavioral health challenges across adolescence and into young adulthood. The genetically informative longitudinal data from a population-based sample with high response rates and multiple ratings, including parent, teacher and peer reports, have provided unprecedented opportunity to characterize the etiology of alcohol use and drinking-related problems across the critical developmental period from adolescence to young adulthood. These data have demonstrated important changes in genetic and environmental influences across adolescence. A fundamental finding is that alcohol initiation in early adolescence is largely influenced by shared environmental factors, with little or no evidence of genetic effects . But as Our data have also demonstrated dramatic modulation of genetic effects as a function of multiple environmental contexts across adolescence, with genetic influences on substance use assuming greater importance under conditions of reduced parental monitoring , high peA series of FT12 studies have characterized effects of early pubertal maturation , behavioThe multiple sources of adolescent assessment in FT12 permitted us to demonstrate shared environmental variance in measured characteristics of home environments . Analyses of drinking patterns at age 14 illustrated cooperative social interaction on abstinence and the peer nomination data from FT12 document significant similarities of peer-assessed behavior of twins and their best friends. Behavioral resemblance was greater in the peer assessments of best friends of MZ cotwins, suggesting that adolescent friendship selection is an active process guided, in part, by our genetic dispositions. Patterns of substance use in early adolescence are especially sensitive to both active selection (adolescents seek to befriend those with behaviors and attitudes matching their own), and reciprocal effects of socialization experiences with the selected peers. A robust predictor of drinking/abstaining in adolescence is drinking or smoking friends, and having friends who drink, smoke, use drugs or engage in delinquent behaviors is more predictive of drinking among girls than among boys.Our data show that girls are more vulnerable to reduced parental modeling, accelerated pubertal maturation and to effects of associating with substance-using peers . Recent A negative relationship  between social anxiety and alcohol dependence was found using ratings of social anxiety from classmate peers at age 12. The protective effect of social anxiety against alcohol problems at age 22 was greater for boys than for girls. But the association of social anxiety at age 12 with smoking frequency at 14 was more strongly negative (more protective) among girls. Another recent analysis used both teacher and repeated self-report measurements across the FT12 waves of assessment to show that alcohol use behaviors at ages 12 and 14 predicted lower educational achievement at later time points, and those associations remained even after previous achievement and measured confounders were taken into account . In anotJointly, these FT12 studies have importantly contributed to our understanding the interplay of genetic and environmental risk factors for alcohol use and problems across adolescence and into young adulthood. With future follow-up of this informatively rich twin cohort, we are developing research protocols to characterize alcohol use patterns, predictors and consequences into early midlife.FT12 data have contributed insights into debate surrounding the gateway hypothesis of substance use/abuse – the hypothesis that early exposure to ‘milder’, legal substances, such as tobacco and alcohol, leads to use of ‘stronger’, ‘illegal’, more addictive substances, including cannabis. In an initial test of that hypothesis , we explTo evaluate the role of externalizing behaviors in the pathway from smoking to drug use, we analyzed whether hyperactivity– impulsivity, aggressiveness, and inattention at 12 predict illicit drug use at age 17 independently, or whether their associations with drug use are mediated through cigarette smoking at age 14 . The assFinally, we examined the role of overlapping genetic and environmental factors in the relationship between early adolescent conduct problems and substance use in young adulthood . We founSmokeless tobacco in the form of snus, a moist powdered pouch tobacco held between lips and gums, is legal in Sweden and has become a popular form of early nicotine exposure in Finland, leading us to test the association between snus experimentation in late adolescence and daily cigarette smoking in early adulthood among men. At age 17, we assessed lifetime use of cigarettes and snus with other potential predictors of cigarette smoking status at young adult follow-up. Analyses focused on 375 men who were never smokers at baseline; when adjusted for age, monthly alcohol intoxication, maternal smoking and peer drug use, snus experimentation increased the likelihood of later daily cigarette smoking nearly four-fold. Results  cannot cDepression and smoking are strongly associated, but the causal nature of their relationship is uncertain. Depression is a major risk factor for suicide and suicidality, but the role of smoking in risk of suicide is equally uncertain. To address these uncertainties, we have examined longitudinal associations between smoking, depression and suicidality using FT12 data. Across the developmental transition from adolescence (age 17) to young adulthood (age 22), we examined bidirectional associations between cigarette smoking and depressive symptoms in nearly 3000 individuals comprising 1154 twin-pairs. At both waves, self-reported depressive symptoms, assessed with the 10-item version of the GBI, and smoking status were analyzed. When adjusted for multiple covariates and baseline depressive symptoms, daily smokers at age 17 had higher depressive symptom scores at age 22 than did never smokers. Similarly, when adjusted for covariates and baseline smoking, a higher GBI score at age 17 was associated with an increased likelihood of being a nondaily smoker or daily smoker at age 22. No associations were found in within-pair analyses, suggesting that the individual-level association is explained by shared familial liabilities .With FT12 data, we examined whether tobacco use in adolescence is associated with intentional self-injury and suicide ideation in young adulthood among 1330 twins. After adjusting for multiple potential confounders, those who reported early onset of regular tobacco use and daily cigarette smoking had a significantly increased risk for intentional self-injury, such as cutting or burning, at age 22 in comparison to those who had not at all initiated tobacco use. Early-onset tobacco use was associated with suicidal ideation in females but not in males. Within-family analyses among twin-pairs discordant for exposure and outcome controlling for familial confounds showed similar, albeit statistically nonsignificant, associations .http://www.action-euproject.eu/). Collaborative and local analyses of aggression using FT12 data have been conducted. The initial consortium publication introduced ACTION’s 11 partners and its main goal: to improve our understanding of the causes of the individual differences in childhood aggression and co-occurring behavioral and emotional problems . Correlations were high between aggression and both externalizing (~.5) and internalizing behaviors (~.4) and generally stable across both age and gender. Co-occurrence patterns were largely similar across countries, instruments and raters; teacher ratings of aggression were studied to investigate aggression and co-occurring behaviors in the school setting using FT12 data and three other ACTION cohorts  and other ACTION consortium analyses utilizing FT12’s genetic, epigenetic and biomarker data are underway  is an understudied but important period for trajectories of behavioral, emotional and physical health. The prospective data, collected on the FT12 sample, make this population-based twin sample an unusually informative one for follow-up study. In view of the increasing recognition of the decade of the 30’s as an important developmental period of the lifespan , it is o


Rheumatoid arthritis (RA) is an incurable disease that afflicts 0.5–1.0% of the global population though it is less threatening at its early stage. Therefore, improved diagnostic efficiency and prognostic outcome are critical for confronting RA. Although machine learning is considered a promising technique in clinical research, its potential in verifying the biological significance of gene was not fully exploited. The performance of a machine learning model depends greatly on the features used for model training; therefore, the effectiveness of prediction might reflect the quality of input features. In the present study, we used weighted gene co-expression network analysis (WGCNA) in conjunction with differentially expressed gene (DEG) analysis to select the key genes that were highly associated with RA phenotypes based on multiple microarray datasets of RA blood samples, after which they were used as features in machine learning model validation. A total of six machine learning models were used to validate the biological significance of the key genes based on gene expression, among which five models achieved good performances [area under curve (AUC) >0.85], suggesting that our currently identified key genes are biologically significant and highly representative of genes involved in RA. Combined with other biological interpretations including Gene Ontology (GO) analysis, protein–protein interaction (PPI) network analysis, as well as inference of immune cell composition, our current study might shed a light on the in-depth study of RA diagnosis and prognosis. Rheumatoid arthritis (RA) is a long-term autoimmune disease that provokes synovial inflammation , through which public data could be integrated and re-analyzed, providing valuable information and novel perspectives regarding different diseases. Thanks to the development of bioinformatics, numerous analytical methods have been implemented for data mining from public databases, among which weighted gene co-expression network analysis (WGCNA) is a well-known approach for gene co-expression analysis. WGCNA was initially proposed by scholars Zhang and Horvath , the corAs a subset of artificial intelligence, machine learning has emerged as a valuable tool in the field of biology, for instance, Le et al.  developeSpecifically, the current study was designed in conformity with the following major points to achieve the intended goal: first, we defined the intersection between hub genes in the training set (determined by WGCNA) and DEGs in the test set as key genes and verified the biological significance of these markers in a tissue sample dataset. Second, the key genes were used as features in machine learning model validation; the key genes were used as features in six different machine learning classification models, the performances of these models were further evaluated, and the biological significance of the key genes was further confirmed.http://www.ncbi.nlm.nih.gov/geo/) on July 15, 2020; we screened GEO microarray datasets in compliance with the following criteria: (1) samples of RA patients and healthy controls (HCs) were collected before receiving pharmacotherapy or other treatments that might affect gene expression profiles; (2) HCs are not necessarily the control used in RA research, as long as these samples represent the gene expression in healthy population. After careful consideration, a total of 12 GEO datasets  was retained and used for integration of 11 training datasets. In order to eliminate potential batch effects that resulted from systematic and non-biological differences among the 11 batches in the training set, we used t-SNE dimensionality reduction algorithm to determine the existence of batch effects. Subsequently, the removeBatch Effect function in the R  package limma (version 3.42.2)   = |cor| based on the gene expression array, after which a weighted undirected network was established using amn (adjacency between gene m and gene n) = smnβ, the appropriate power parameter β = 8 was determined by pickSoftThreshold function    was defined.The GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of DEGs was implemented by the R package clusterProfiler (version 3.14.3)  algorithm was performed on the key genes to select the modeling feature. LASSO was implemented by glmnet package (version 4.0.2)  and DEGs of the test set . The expAfter the analysis with CIBER-SORT, inferred immune cell compositions in the RA and HC groups were visualized ; the corOur machine learning methods were based on pre-defined key genes. First, LASSO algorithm was used for selection of pivotal key genes that were appropriate for subsequent machine learning validation; the λ value corresponding to the smallest binomial deviance was selected as the penalty coefficient, whereby 15 features were obtained for building the predictive model . The weiIn this study, we first identified numerous DEGs (between RA patients and controls) in the training set/test set. Gene modules (blue/turquoise modules) strongly associated with RA in the training set were subsequently discovered by WGCNA, whose intersection with DEGs in the training set was defined as hub genes. Network analyses revealed the correlation among hub genes at both transcriptome (WGCNA node score) and protein (PPI network combined score) levels. Afterward, the intersection between DEGs in the training set and hub genes was defined as key genes and underwent selection by LASSO algorithm before being used as features in machine learning model validation. Finally, the biological significance of these features was supported by relatively high AUC (>0.85) achieved by 5 out of 6 machine learning models.In 11 GEO datasets based on blood samples (training set), we discovered a total of 451 DEGs that were significant between RA patients and controls, among which 231 upregulated and 220 downregulated genes were screened using a stringent threshold. These DEGs underwent subsequent GO term enrichment and KEGG pathway analysis, through which we further discovered several pathways where DEGs were significantly enriched. As for BP, DEGs were related to neutrophil associated pathways. Neutrophils play a pivotal role in the initiation of RA; these cells will be activated after migrating into the articular cavity where they exert regulatory functions, such as generating cytokines that affect other immune cells, thereby sustaining the inflammation status and contributing to the pathogenesis of RA  exhibited the most significant positive/negative correlation with the sample status; therefore, these two modules were merged together as module genes for in-depth study. Pathway enrichment analysis of these modules showed that: 1, consistent with the results of DEGs, both modules were mainly enriched in neutrophil associated process with regard to BP category; 2, for CC, genes in the blue module were predominantly implicated in adhesion and junction, whereas genes in the turquoise module were clustered in lumen, agreeing with the result of DEGs; 3, in terms of MF, genes in the blue module were responsible for NADH dehydrogenase activities, whereas genes in the turquoise module participated in various molecular binding activities, especially ubiquitin protein ligase binding; 4, similar to DEGs, genes in the blue module were mainly associated with neurodegeneration-associated KEGG pathways, whereas genes in the turquoise module were connected with immune-associated KEGG pathways [nuclear factor (NF-kappa) B signaling pathway/T cell receptor signaling pathway]. Collectively, pathways in which genes in the blue module were enriched  were positively correlated with RA, whereas their turquoise counterparts  were quite the opposite. Some supporting evidence was discussed below: the expression of several adhesion molecules was previously discovered in rheumatoid synovium, and these molecules promote the pathogenesis of RA through regulating synovial production Haskard, ; the mutEnrichment analyses were performed to interpret the biological significance of the newly defined set of genes; the majority of results concerning BP, CC, and KEGG pathway analysis were highly consistent with that of DEGs or blue/turquoise modules, except for enrichment in GO MF terms that varied across a wide range of MFs, including binding functions  and regulation of enzyme activity . Some of these functions were also related to arthritis: research on pre-RA subjects and matched controls in a cohort study showed that erythrocyte membrane levels of the n−6 polyunsaturated fatty acids—linoleic acid (PUFA LA) were inversely associated with RA development  and downregulated  key genes. As expected, these key genes exhibited similar expression patterns in tissue samples; we discuss their potential roles in RA based on our current results in the following lines. FUT7 gene encodes fucosyltransferase-VII, an important mediator for synthesizing selectin ligands    is secreted by Th1 (CD4+) cells, and the inverse correlation between IFN-γ and IK1/Kir2.1 expression was found in the rat heart with myocardial infarction, where Th1 cells responded to the stimulation by elevating the level of IFN-γ; the regulatory role of CD4 cells on IK1/Kir2.1 expression was therefore ascribed to IFN-γ -like transcript 2 (TLT-2), is stably expressed by CD8(+) T cells, when binding to T cell proliferation co-stimulator B7-H3 (CD276)  through the tau pathology pathway  encodes tristetraprolin (TTP), a negative regulator of many pro-inflammatory genes, including TNF-α that participated in the pathogenesis of RA and other inflammatory diseases   and DEGs of the test set. However, TNFSF10 and VEGFB, respectively, belong to two established RA-associated protein families, namely, TNF superfamily and vascular endothelial growth factor (VEGF) family. TNFSF superfamily is involved in the simulation of several immune cells (including T and B lymphocytes) and therefore considered a hallmark of autoimmune diseases  T cells and M1 inflammatory macrophages, respectively) in RA tissue samples. Intriguingly, in RA tissues, the percentage of resting CD4(+) memory T cells in RA was significantly reduced by comparing the elevated proportion of activated CD4(+) memory T cells, such trade-off suggested that resting CD4(+) memory T cells might be activated in response to the inflammatory stimulation of RA. These results indicated that the change in RA immune microenvironment might be associated with our currently identified key genes. Collectively, among the six top key genes, to our knowledge, FUT7 and ZFP36 were previously reported to be related to RA, whereas TREML2, KCNJ2, and BIN1 might be associated with inflammatory response. The one remaining gene PNPO is a novel potential RA biomarker predicted in the current study. The elevated TREML2 and FUT7 expression was consistent with the inference of CIBER-SORT immune cell alteration.As an autoimmune disease, the onset of RA is accompanied by a series of immune processes, wherein immune cells play a fundamental role. To gain a deeper understanding of the key genes, we sought to link the expression patterns of the key genes with immune cells by analyzing the immune cell composition in tissue samples. The promoted local recruitments of five types of immune cells in RA tissues were inferred by CIBER-SORT, among which increased proportions of CD8(+) T cells and M1 inflammatory macrophages were consistent with the verification regarding 2 out of 3 top upregulated genes (elevated TNFSF10 (the key gene identified in the current study) was also among the top 10 characteristic genes (without heterogeneity between two datasets) reported by Xing et al.  RA patient samples, we used the LASSO penalized model to further select pivotal key genes that were appropriate for subsequent validation. A total of 15 pivotal key genes were selected, and, as expected, the top three up/downregulated  key genes were also incorporated. These biomarkers were used as features to train multiple machine learning algorithms to validate their biological significance. Previously, WGCNA and machine learning were used to uncover causative factors in RA; for instance, Ma et al.  used twog et al. ; Ma et ag et al.  used Bayg et al.  adopted Likewise, studies of machine learning had attained successes in the prediction of RA, for instance, histologic data were used to establish machine learning model for stratifying synovial subtypes of RA  were validated by machine learning model validation, and the results showed that aside from “RF,” AUC of multiple machine learning methods  exceeded 0.85, especially BPNN (with an AUC of 0.99), which was higher  than the AUC achieved by the aforementioned reports. As suggested in previous review, eliminating redundant features and focusing on fewer elements that are relevant to the phenotypes could improve the performance of a classifier, as empirical knowledge was incorporated into the procedure ; therefore, posttranslational modulations that play pivotal roles in the pathogenesis of autoimmune diseases including RA (Opdenakker et al., FUT7 (Li et al., ZFP36 (Taylor et al., TNFSF10 (Croft et al., VEGFB (Taylor, TREML2 (Chapoval et al., KCNJ2 (Li et al., BIN1 (Chang et al., TREML2 and FUT7 exhibited expression patterns that were consistent with our current inferential results of immune cells composition, whereas PNPO is not yet reported in RA and deserves further investigation. The preceding key genes were among the 15 pivotal features selected by LASSO, and their biological significance was further confirmed through machine learning model validation. Taken together, our currently identified key genes might provide novel perspective in understanding RA pathogenesis or serving as biomarker for RA diagnosis. Their correlation with immune response/immune cells also confers them the potential as therapeutic target of RA, since the suppression of harmful properties in immune cells has been proposed as a feasible approach to alleviate RA through preventing inflammation (Xue et al., In summary, the present study discovered several enriched pathways in RA patients based on DEGs, and the corresponding hub genes were determined by WGCNA and visualized using the PPI network. By incorporating the genetic information from the test set, 22 key genes were subsequently defined, among which  Taylor,  belongedThe original contributions presented in the study are included in the article/JX and RW wrote the manuscript and interpreted the data. XC contributed to the analysis of data and drafted the manuscript. ZY designed the study and revised the manuscript. All the authors have read and approved the final version of the submitted manuscript.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.


Bronchopulmonary dysplasia (BPD) is a severe pulmonary complication of prematurity and is associated with significant morbidity or death. Early use of systemic corticosteroids may alter the trajectory of the disease and improve outcomes. A BPD Outcomes estimator, developed by the NICHD using a large population dataset, can be used to calculate individual risk. Risk above a certain threshold may indicate that the benefits of corticosteroids outweigh the risks. Empiric analysis of this calculator by systematic entry of synthetic patient information reveals a marked racial disparity; black infants have lower risk of moderate/severe BPD due to a higher risk of death despite equivalent severity of illness. Interpretation and analysis of this finding can be found in “The challenge of risk stratification of preterm infants in the setting of competing and disparate healthcare outcomes” 2), is reported.In this report, we provide the underlying data used in this analysis. Calculator output for 108 example patients, systematically varied by sex, birthweight, race, type of ventilator, and fraction of inspired oxygen (FiO Specifications Table•These data highlight an obstacle in application of the output of the NICHD BPD Outcomes estimator because black infants have a consistently lower predicted risk of BPD due to a higher risk of mortality.•Neonatologists, Pulmonologists, and Pharmacists developing postnatal corticosteroid treatment algorithms will benefit from the knowledge that this disparity exists.•These data suggest that applications of BPD risk calculators should incorporate the difference in mortality risk by use of an alternate threshold or an expanded metric.•These data further demonstrate that sociodemographic factors can have a powerful influence on NICU outcomes, and that care should be taken when developing calculators or guidelines to ensure that disparities which drive differences in outcomes are accounted for in risk assessment.1A single table of data is provided. Each row represents a single patient, with systematic variation of each clinical factor except for gestational age (which is held constant at 24 weeks). Column 1 is a unique identifier, columns 2-8 encompass clinical and demographic factors, while columns 9-14 provide the calculated risk of death, severe BPD, moderate BPD, mild BPD, no BPD, and combined risk of moderate/severe BPD.2https://neonatal.rti.org/index.cfm?fuseaction=BPDCalculator.start). This tool uses clinical and outcome data collected between 2000-2004 from 3629 preterm infants born before 30 weeks gestation 2. Based on these data, the calculator then outputs the predicted probability of five different outcomes .These values were obtained from the NICHD BPD Outcomes estimator  and high-frequency oscillatory ventilation (HFOV); FiO2 was incremented in 10% blocks from 21 to 100%.The goal of this project was to systematically vary the input variables to evaluate the calculator response. Two variables were held constant in all trials , while sex, race, ventilator type, and FiOThe calculated risk of each of the 5 outcomes was recorded in the table. A meta-analysis by Doyle