Colorectal cancer (CRC) causes the second most cancer deaths worldwide, but the disease course varies according to tumour characteristics and immunological factors. Our objective was to examine the associations of tumour necrosis with tumour characteristics, immune cell infiltrates, serum cytokine concentrations, as well as prognosis in CRC.Three independent CRC cohorts, including 1413 patients, were analysed. Associations of the areal percentage of tumour necrosis with clinicopathologic parameters, tumour infiltrating immune cells, cytokine concentrations in systemic and mesenteric vein blood, and survival were examined.BRAF status, and other possible confounding factors. In the largest cohort (N = 1100), the HR for high tumour necrosis percentage (≥40% vs. <3%) was 3.22 . Tumour necrosis percentage positively correlated with peripheral serum levels of CXCL8, a proinflammatory chemokine, and negatively correlated with mesenteric serum levels of CXCL10 and mast cell densities in the invasive margin of the tumour.Higher tumour necrosis percentage associated with shorter colorectal cancer-specific survival independent of tumour grade, T, N or M-class, mismatch repair status, Our results support the value of tumour necrosis as a prognostic factor in colorectal cancer. CXCL8 may have a role in the systemic effects of tumour necrosis. BRAF, and RAS mutation status [Colorectal cancer (CRC) is the third most common cancer in the world, and it causes the second most cancer deaths worldwide . The pron status . HoweverColorectal cancers frequently contain some amounts of necrosis, and tumour necrosis is a negative prognostic factor in CRC . The locThe aim of this study was to (a) evaluate the independent prognostic role of tumour necrosis in CRC, and to (b) investigate the local and systemic alterations of immune and inflammation-related biomarkers associated with tumour necrosis. We analysed three different cohorts: Cohort 1 consisted of 1100 CRC patients with comprehensive clinicopathologic annotations and long follow-up for survival analyses; Cohort 2 consisted of 287 patients, from whom more detailed immune cell types and peripheral cytokine levels were analysed; and Cohort 3 consisted of 26 patients that had peripheral and mesenteric venous blood samples analyzed in a unique study setup, enabling more direct analysis of the tumour-derived factors entering the circulation. Our focus was to clarify the reaction patterns (cytokine secretion and immune cell infiltration into tumours) tumour necrosis elicits in the host, as well as their impact on the disease course.Three independent cohorts were analyzed Fig. .Fig. 1TuN = 357) operated on at Oulu University Hospital between 2006 and 2014 [Cohort 1 was retrospectively collected in Central Finland Central Hospital in Jyväskylä, consisting of 1343 patients who had undergone tumour resection during 2000–2015 and from whom adequate tumour samples were available , 7. Cohoand 2014 , 9.N = 243; Cohort 2: N = 70) were excluded from further analyses, and patients who died in less than 30 days after surgery  were excluded from survival analyses, thus data of 1063 or 1100 patients from Cohort 1 and data of 284 or 287 patients from Cohort 2 could be utilised. Clinical endpoints were cancer-specific survival (CSS), defined as the time from surgery to cancer death or to the end of follow-up and overall survival (OS) defined as the time from surgery to death or to the end of follow-up. The median follow-up time for censored cases was 10 years . In addition of offering validation for survival analysis, Cohort 2 provided information about the tumour immune cell profile and cytokine levels in the systemic circulation.Patients who had received preoperative radiotherapy or chemoradiotherapy  was used to measure serum cytokine levels , and theIn addition, IL6 was excluded from the Olink results, as 50 of the measurements in Cohort 2 (2010–2014) and 15 in Cohort 3, were outside the assay working range or did not meet quality control criteria. For Cohort 3 patients, additional peripheral/mesenteric cytokine concentration difference values were calculated by subtracting peripheral vein serum values from mesenteric vein serum values, to measure the difference in cytokine levels between systemic blood and mesenteric vein blood.BRAF V600E mutation status were assessed using immunohistochemistry as described earlier [Haematoxylin & eosin staining was used in analysing the tumour specimens that were fixed in 10% formalin and then embedded in paraffin. TNM stage was determined by the UICC/AJCC  criteria and grade according to the WHO criteria. The Glasgow Microenvironment score (GMS) was evaluated , compose earlier –17.The analyses of immune cell densities in tumour samples, based on immunohistochemistry and quantitative image analysis, have been described earlier. For Cohort 1, tumour infiltrating T cells were quantified by using QuPath bioimage analysis software . It usedP < 0.05 statistically significant.Statistical analyses were carried out using IBM SPSS Statistics for Windows (IBM Corp. version 27.0). We considered findings with two-sided BRAF V600E mutation status , tumour location , and stage . In Cohort 3, only age (continuous) and Stage  were included, considering the lower sample size. The continuous variables with positive skewness were logarithmically transformed. The linearity, normality, and homoscedasticity assumptions were checked by using normal probability plot of residuals and scatterplots of residuals compared to predicted values. The statistical significance of the associations between MMR status and immune cells were determined by using the Mann–Whitney U test.Crosstabulation was used to investigate the associations between tumour necrosis percentage categories and tumour and patient characteristics. The tumour necrosis percentage was categorised into four classes <3%, 3–9.9%, 10–39.9% and ≥40%, in accordance with a previous study [BRAF V600E mutation status , tumour location , time of operation , lymphatic or venous invasion , and grade . We excluded patients who died within 30 days of having surgery .Cox regression models and Kaplan–Meier estimates were used to assess the associations of tumour necrosis categories with cancer-specific and overall survival. The assumptions for Cox regression model were checked by inspecting Schoenfeld residual plots that supported the proportionality of hazards during the 10-year follow-up. Multivariable Cox regression models included the following pre-determined covariates: age , sex , T , N , M , MMR enzyme status , P < 0.0001), tumour location in the distal colon (P = 0.0001), high Glasgow Microenvironment Score (GMS) (P < 0.0001) and high disease stage (P < 0.0001). High tumour grade (P = 0.0003), and the presence of nodal (P = 0.0002) and distant metastases (P = 0.042) were also associated with high tumour necrosis percentage. MMR deficiency and BRAF V600E mutation were associated with low tumour necrosis percentage . Overall, high tumour necrosis percentage appeared to be associated with several adverse tumour characteristics.We first analyzed the associations of tumour necrosis with tumour and patient characteristics in 1100 patients of Cohort 1 (Table P < 0.0001) .In 10-year survival analyses, there were 530 (49.9%) deaths of which 295 (27.8%) were cancer deaths. Kaplan–Meier survival functions showed a significant association between tumour necrosis categories and survival, especially in the CSS analysis   Supplem, which iP = 0.0013) independent of disease stage, MMR status, and other tumour and patient characteristics .P < 0.0001), high grade (P < 0.0001) and MMR proficiency (P < 0.0001). There was more statistical power in Cohort 1 due to the higher numbers, which might explain why parameters like tumour location and BRAF mutation did not show statistically significant associations in Cohort 2.In the validation cohort, mainly similar associations were seen between tumour necrosis percentage and clinicopathologic features, as in Cohort 1 (Supplementary Table P < 0.0001 for both) (Table Ptrend = 0.018)  deaths and 76 26.8%) cancer deaths in Cohort 2. As in Cohort 1, high tumour necrosis percentage was associated with shorter CSS and OS in univariable analysis (6.8% canc8) Table .P = 0.226). Instead, mast cell densities in the invasive margin were negatively correlated with tumour necrosis percentage , while CD3 + , CD8 + or FOXP3 + T cells, and neutrophils did not show significant correlations in the multivariable models. We also analyzed immune cell densities in relation to MMR status. The number of immune cells was higher in tumours that were MMR-deficient . Of other cytokines, tumour necrosis percentage positively correlated with IL7 in Cohort 2B but not in 2 A , and with IL6 in Cohort 2A .We then aimed to characterise the associations between tumour necrosis percentage and systemic inflammatory markers Table . For theP = 0.465), related to the smaller sample size. CXCL8 concentrations were frequently higher in the mesenteric venous blood compared to the peripheral blood, and the positive correlation between tumour necrosis and mesenteric serum CXCL8  was stronger than with peripheral CXCL8. The CXCL8 difference variable  also showed a tendency towards a positive correlation with tumour necrosis percentage .Finally, we utilised a unique study setup of mesenteric venous blood sampling during operation from 26 patients to evaluate the associations of tumour necrosis with circulating inflammatory mediators near the tumour site. Patient characteristics are presented in Supplementary Table P = 0.022), but there were no statistically significant correlations between tumour necrosis percentage and any of the difference  variables.Of the other cytokines, tumour necrosis percentage negatively correlated with CXCL10 levels in the mesenteric serum , and a trend towards a negative correlation between tumour necrosis percentage and IFNG . These associations may also reflect the suppression of local anti-tumour inflammatory response in necrotic tumours, considering that CXCL10 and IFNG are regarded as important cytokines in the antitumorigenic T helper type 1 response [CD3 + T cell densities showed a weak negative correlation with tumour necrosis percentage in Cohort 1, but this was not confirmed in Cohort 2. Tumour necrosis also associated with a weaker lymphocyte infiltration in CRC patients with TNM stage IV without residual disease . We founresponse . Furtherresponse .CXCL8 [Peripheral serum CXCL8 levels were found to have positive correlation with tumour necrosis percentage, and such tendency was also observed between the mesenteric vein serum CXCL8 and tumour necrosis percentage, suggesting that CXCL8 may transmit the protumor signals related to tumour necrosis. Previous studies also support the role of CXCL8 in tumour progression: CXCL8 enhanced tumour proliferation rate, angiogenesis and the ability to metastasize , 39; recCXCL8 . In hepaCXCL8 . InhibitIncreased systemic inflammation and reduced local inflammation in tumours with abundant necrosis have also been reported in some previous studies , 44. OthBRAF status. We compared necrosis percentage and the GMS to establish if necrosis percentage can be used as an additional parameter to supplement the prognostic information of the GMS. We discovered that these parameters represent independent, complementary prognostic factors in CRC. Tumour necrosis percentage has potential to become a predictive biomarker in the future; further studies should assess whether tumours with high necrosis percentage would benefit from specific chemotherapies. For some histological parameters, such as tumour budding in colorectal cancer [We found that high tumour necrosis percentage was associated with shorter cancer-specific survival in two independent cohorts, involving more than 1300 patients. Several previous studies have also suggested that tumour necrosis represent a potential prognostic factor in CRC –28, 45. l cancer , consensSeveral limitations of our study must be considered. First, imprecision in the necrosis data might exist, as pathologists usually prefer to sample tumour regions that are not overly necrotic. The necrosis percentage was visually assessed, which may yield some variability in the interpretation. However, these variations are expected to have a nearly random distribution, which would drive our results towards the null hypothesis. Second, tissue microarrays were utilised to analyse immune cell densities, and they are not representative of the overall immune cell infiltrates of the tumours. However, immune cell densities evaluated by tissue microarrays have been shown to be strongly associated with patient survival in CRC , supportBRAF status.In conclusion, tumour necrosis is associated with high circulating CXCL8 concentrations, suggesting that CXCL8 could contribute to the pro-tumour systemic effects of tumour necrosis. Our study supports the value of tumour necrosis as an adverse prognostic factor in CRC independent of disease stage, lymphovascular invasion, tumour grade, MMR status, and Supplementary online material


It is observed that gate voltages applied to the Fex3-GeTe2/In2Se3 heterostructure device modulate the magnetic properties of Fex3-GeTe2 with significant decrease in coercive field for both positive and negative voltages. Raman spectroscopy on the heterostructure device shows voltage-dependent increase in the in-plane In2Se3 and Fex3-GeTe2 lattice constants for both voltage polarities. Thus, the voltage-dependent decrease in the Fex3-GeTe2 coercive field, regardless of the gate voltage polarity, can be attributed to the presence of in-plane tensile strain. This is supported by density functional theory calculations showing tensile-strain-induced reduction of the magnetocrystalline anisotropy, which in turn decreases the coercive field. Our results demonstrate an effective method to realize low-power voltage-controlled vdW spintronic devices utilizing the magnetoelectric effect in vdW ferromagnetic/ferroelectric heterostructures.We investigate the voltage control of magnetism in a van der Waals (vdW) heterostructure device consisting of two distinct vdW materials, the ferromagnetic Fe The control of magnetism by electric field is an important goal for future development of low-power spintronics. Here, the authors demonstrate voltage control of magnetism in van der Waals ferromagnetic/ferroelectric heterostructure devices via the strain-mediated magnetoelectric effect. The interactions between the distinct magnetic and electric order parameters, along with the associated atomic, ionic, or molecular structure, can result in emergence of rich and intriguing physical phenomena. An effective strategy to achieve the magnetoelectric effect is to combine materials with distinct ferroic orders. For instance, in a ferromagnetic/ferroelectric composite system, the electric-field-controlled polarization or strain in the ferroelectric can induce modulation of the magnetic properties in the adjacent ferromagnet12. When utilized in nano-electronic devices, these composite systems offer multifunctional and advanced device characteristics that cannot be attained by the constituent materials independently13.The magnetoelectric effect is a classical topic in material science and physics. In magnetoelectric materials, the electric and magnetic properties are coupled: the magnetic moments (electric dipoles) can be manipulated by the electric (magnetic) field15. (2) Various fundamental material properties of two-dimensional (2D) vdW materials can be functionally controlled through strain, gating, proximity effect, and twist angle, which facilitates the controllability of vdW materials via external methods16. (3) The weak interlayer magnetic interactions make vdW ferromagnets an ideal material platform to investigate interfacial interactions, i.e., the coupling at the ferromagnetic/ferroelectric interface can play a more prominent role since the ferroic orderings within the component materials are not too strong. A recent study shows that interfacial magnetic effects can indeed be enhanced when the interlayer magnetic coupling is weak17.In this article, we experimentally demonstrate the magnetoelectric effect in a van der Waals (vdW) material heterostructure, consisting of a ferromagnetic and a ferroelectric vdW material. Ferromagnetic/ferroelectric vdW heterostructures offer unique advantages over conventional thin-film-based composite systems to investigate the magnetoelectric effect. (1) Heterostructures composed of various families of vdW materials can be readily fabricated by mechanical exfoliation, transfer, and stacking, which makes it possible to investigate new functionalities arising from the interplay between symmetry-breaking orderings, that are separately present in the constituent materials, through interfacial coupling22. Yet, the voltage-controlled magnetoelectric effect in vdW heterostructures, consisting of two functional vdW materials, has not been experimentally demonstrated so far.Given these advantages, it is natural to conceive a vdW-material-based device consisting of a ferromagnetic and a ferroelectric vdW material in which the change in the polarization by applied electric field can modify the properties of the ferromagnet by interfacial coupling. In fact, theoretical studies suggest the possibility of magnetoelectric interactions between vdW materialsx3-GeTe2 (x ≈ 0.36) layer and a ferroelectric α-In2Se3 layer. Fex3-GeTe2 (FGT), which is a hole-doped version of Fe3GeTe224, is a vdW ferromagnetic metal with bulk Curie temperature TC around 150 K and perpendicular magnetic anisotropy27. Large doping-dependent modulation of TC and coercive field is reported; these doping effects are closely related with the change in magnetocrystalline anisotropy induced by shifts in the energy bands28. This intricate relationship between electronic structures and magnetic anisotropy facilitates the capability to electrically control magnetism by changing the electronic structures, as the magnetic anisotropy acts as an energy barrier in the magnetization switching process. The non-centrosymmetric α-In2Se3 (IS) is a vdW semiconductor that exhibits room temperature ferroelectricity, showing a relatively small ferroelectric coercivity of ~2 × 107 V m−132. Due to the voltage-dependent expansion of in-plane lattice constants35, a large piezoelectric effect is expected which allows the control of in-plane strain and surface charges by applied voltage.Here, we study the voltage control of magnetism in a vdW heterostructure device consisting of a ferromagnetic Fe36, e.g., 2D versions of energy-efficient magnetoelectric spin–orbit (MESO) devices, recently proposed in the semiconductor industry13.In our experiments, the magnetic properties of FGT are measured while applying an external voltage to the FGT/IS vdW heterostructure, using a magneto-optic Kerr effect (MOKE) microscopy system. We find that the magnetic properties of FGT show a sizeable voltage-dependent change where the decrease in coercive field is observed in both positive and negative voltages. This unusual homopolar behavior is further investigated by voltage-dependent Raman micro-spectroscopy which confirms the existence of piezoelectric strain in the FGT/IS heterostructure providing tensile strain for both positive and negative voltages. The link between the strain and magnetic properties of FGT is investigated by first-principles density functional theory (DFT) showing substantial decrease in the magnetocrystalline anisotropy with tensile strain, which can account for the reduction of the magnetic coercivity. Our experiments and calculations demonstrate a new method of voltage-controlled magnetism via strain coupling in a vdW ferromagnetic/ferroelectric heterostructure. Furthermore, our realization of a vdW magnetoelectric device signals a major advance towards developing low-power all-2D-material-based spintronic devices39, such that it may in fact help transfer in-plane strain from the IS to FGT in this work (see “Discussion” section).Figure VG) is applied across the IS between the FGT (top electrode) and graphite (bottom electrode); the top FGT is grounded such that negative (positive) VG denotes the FGT being at higher (lower) electric potential. The VG-dependent gate current (IG) flowing through the IS, measured under the illumination of laser at 70 K, exhibits a diode-like behavior  is consistent with the perpendicular magnetic anisotropy of FGT reported previously42.A gate voltage  of the FGT (Fe2.64GeTe2) used in this work, which is a hole-doped version of Fe3GeTe2. Upon voltage application, the FGT magnetic properties exhibit an intriguing VG-dependent change  decreases as VG increases . For the negative VG case, Hc again decreases as the magnitude of VG increases /h-BN(10 nm) heterostructure device at 67 K, in which a paraelectric and insulating h-BN replaces IS. Here, the loops are unaffected by VG up to ±14 V  adjacent to FGT is essential for the emergence of the voltage effect on the FGT magnetic properties.In an effort to verify the role of the IS in the 4 V Fig. , showingGiven the homopolar voltage dependence of magnetic properties and absence of voltage-dependent change in the centrosymmetric substrate, we propose the interfacial coupling that transfers the strain developed in IS to FGT as the origin of the observed non-remanent voltage effect in the magnetic properties of FGT. The Raman analysis and DFT calculations that follow will confirm this. Other possible interpretations, such as current-induced effects or interfacial charge from the out-of-plane polarization, are excluded based on our experimental results.TC of the FGT in the heterostructure devices. In SI Fig. STC of the FGT flakes are ≈120 K at zero bias, and the TC shows little change with voltage application (VG = ± 4–5 V). In the discussions following the Raman analysis, we further rule out the possibility of current-induced Joule heating effects. Second, current-induced spin-torque effects can be excluded: the current density flowing through the FGT/IS hetero-junction is ~ 106 A m−2, which is ~ 5 orders of magnitude smaller than the ~1011 A m−2 current density typically required for any significant spin-transfer-torque or spin–orbit-torque effects to occur. Additionally, we do not observe any electrically induced Hc change in the region of the same FGT/IS heterostructure device where the ferroelectric IS is absent, even when the same level of current is flowing through the region  of IS is identical regardless of voltage polarity as long as the external electric field (±6 V in this work) is much larger than the ferroelectric switching field of IS 40; in such condition, the polarization is always kept parallel to the external field such that the sign of the converse piezoelectric coefficient remains the same. The amplitude of in-plane lattice expansion/contraction is determined not by the direction but by the amplitude of the out-of-plane polarization. This change in the in-plane lattice constants provides strain to the FGT by interfacial coupling, which can induce the VG-dependent Hc modulation in the FGT/IS heterostructure.The homopolar behavior of VG. Raman micro-spectroscopy is a useful technique to study the local strain state of micrometer-sized flakes, since the characteristic wavenumber of phonon modes are sensitive to lattice expansion/contraction45. Figure VG-dependent Raman shift measured at 70 K, i.e., approximately the temperature at which the MOKE measurements are performed. We observe four peaks within the Raman shift range of 80–160 cm−1 where the Raman modes at zero bias (VG = 0 V) are indicated by vertical lines. This region of spectra allows easy tracking of both FGT and IS peaks depending on a voltage bias: two peaks observed at ~96 and ~110 cm−1 originate from the E and A1 modes of α-IS46, and the other two peaks located at ~132 and ~148 cm−1 correspond to FGT47. The comparison between spectra obtained at 70 K (solid curves) and 300 K  clearly shows the temperature-dependent Raman peak positions moving towards lower wavenumbers (or redshift) as the temperature increases; for example, the strongest IS peak is observed at 103 cm−1 at room temperature , such that the amount of redshift is ~7 cm−1 per 230 K. This redshift of the Raman peak positions is mainly due to the lattice expansion of each material and consistent with previous reports50.In order to observe the voltage-dependent strain modulation in the heterostructure, its Raman spectra are measured as a function of VG, which would result in changes to the Raman peak positions. In order to observe any VG-dependent Raman peak position change, the VG-dependent Raman spectra are fitted with the multiple-Voigt-function model; the IS and FGT peak positions are shown as dotted gray lines in Fig. VG. For all the IS and FGT Raman peaks, we see the same trend with voltage. When VG is applied, the Raman peak positions of both IS and FGT decrease (redshift) compared to the zero bias case, regardless of polarity. This implies that the interfacial coupling between the IS and FGT layer is strong enough, such that the piezoelectric response of the IS layer is transferred to the ferromagnetic FGT layer. By analogy with the thermal-expansion-induced redshift (see previous paragraph), and from the fact that the in-plane lattice of IS expands as the out-of-plane polarization increases 35, the voltage-induced redshift of the Raman peaks corresponds to an in-plane tensile strain in the heterostructure. We estimate the tensile strain of IS to be 0.3–0.4 % at VG = 5 V, based on the rate 3.1 cm−1/% of Raman shift change with respect to strain, derived by Guo et al.51 While the FGT Raman peak redshift suggests the presence of tensile strain in FGT, the exact amount of strain in the FGT cannot be estimated due to lack of earlier studies on Raman measurements of the strain state of FGT.The piezoelectric IS layer can generate strain in response to the varying VG-induced Raman peak redshift disappears when the bias is decreased back to zero  of the IS flake (±1 V)30. While the increase of Ec is expected at low temperatures, other well-known room temperature ferroelectric materials  show 30–100% increase of Ec at cryogenic temperatures compared to room temperature52, such that the voltages we applied for the MOKE and Raman measurements are likely larger than the Ec of the IS flake even at 70 K. Also, note that the thermal effect due to Joule heating cannot explain the VG-induced peak position change in Raman spectra since the FGT peaks are generally insensitive to temperatures below ~140 K47. Furthermore, in case the Raman peak position change is purely due to Joule heating, the amount of change in the peak positions we observe  would correspond to at least 30 K, assuming a linear relation between the data points at 70 and 300 K; this value is unreasonably large considering the small IG observed in the device. Therefore, we believe the VG-induced tensile strain in the FGT/IS heterostructure is the most likely origin of the consistent Raman peak redshifts that we observe.The polarization-induced surface charge modulation at the FGT/IS interface can once again be excluded by measuring the Raman spectra of the remanent states at zero bias after voltage application, which shows that the SI Fig. S. Note thHc) and the tensile strain in the FGT/IS heterostructure device show consistent voltage dependence. This suggests that the IS piezoelectric strain and accompanied change in lattice constants modulates the Hc of the adjacent FGT. In general, Hc of magnetic materials are determined by many material parameters, including the magnetic anisotropy, magnetization, magnetic domains, defects, etc. However, it is not likely that there will be voltage-induced changes in the defect states of the metallic FGT. We also argue that any voltage-dependent modulation of the magnetic domains would likely be a consequence of changes in the magnetic anisotropy53. Thus, it is reasonable to expect the observed reversible voltage-dependent change of Hc can most likely be attributed to a voltage-controlled modulation of either the magnetization or the magnetic anisotropy54.From the experiments, it is clear that both the magnetic properties  (see “Methods” section and ref. 28 for details). Figure Hc. We point out that the hole doping due to the Fe deficiency in our FGT specimen is crucial for this large strain-induced change in the MAE. That is, the hole doping decreases the overall MAE and drives the system in close proximity to the tensile strain-induced transition from out-of-plane to in-plane magnetocrystalline anisotropy. As the hole doping decreases, the MAE can become relatively insensitive to the strain, or in some cases show a tensile-strain-induced MAE increase  is investigated by first-principles density functional theory (DFT), which reveals the existence of a substantial tensile-strain-induced decrease in the FGT perpendicular magnetocrystalline anisotropy. We assume 1 hole doping (h) per formula unit (f.u.) corresponding to the Fe-deficiency x ≈ 0.36 mostly on the Feξk is defined asN is the number of k-points, and ξk integrated over the Brillouin zone (BZ) comes to be the MAE, by analyzing the ξk, we can identify k-points that mainly contribute to the MAE and also the momentum-dependent MAE changes with tensile strain. Figure k. We find that for both unstrained and strained cases, the k-dependent pattern. As the k-vector moves away from the Γ-point, there is an alternating contribution to MAE, with negative (positive) values for small (large) magnitude of k-vectors. In the vicinity of the K-point, there is also substantial contribution to MAE, with positive MAE contribution in close proximity to the K-point and negative MAE further away from the K-point. When all the contributions in the in-plane BZ are summed, the overall MAE changes sign from positive (perpendicular anisotropy) to negative (in-plane anisotropy) with a large 1% tensile strain as shown in Fig. k-dependent MAE between the unstrained and strained cases reveals that the negative MAE contributions around the Γ-point dominate, resulting in a net negative change in MAE.Further investigation of the strain-induced change in the electronic structures  reveals that the tensile strain induces the momentum-dependent band shifts. This results in the decrease (increase) in MAE around the Γ(K)-point, with the net effect being the decrease in the overall MAE. The momentum-resolved MAE εnk around the Fermi energy, Eq. . Nevertheless, we obtain consistently similar polymer thickness under our sample fabrication conditions  we use in our work, but the MAE increases with strain for lower-level-hole-doping cases in agreement with the tensile-strain-induced Hc increase in the un-doped Fe3GeTe2 observed by Yu Wang et al.55In fact, in an earlier studyIn conclusion, we investigate the voltage control of magnetism in a vdW ferromagnetic/ferroelectric FGT/IS heterostructure device. Voltage-dependent MOKE measurements on the heterostructure device show a decrease in FGT coercive field for both positive and negative biases, while voltage-dependent Raman spectroscopy reveals the existence of voltage-dependent tensile strain states of FGT and IS, regardless of voltage polarity. The consistent voltage-dependent change in both the magnetic properties and strain state suggests that the voltage-induced piezoelectric strain in IS gives rise to changes in the magnetic properties of the adjacent ferromagnetic FGT. Density functional theory calculations show a large strain-dependent change in the FGT magnetic anisotropy energy, confirming the coupling between strain and magnetism in a vdW ferromagnetic/ferroelectric heterostructure.2.64GeTe2 (FGT) are grown from molten metallic fluxes, as reported previously25. Single crystals of graphite, h-BN, and 2H α-In2Se3 (IS) are commercially available from HQ Graphene.Single crystals of Fex layer. Au (100 nm)/Ti (5 nm) electrodes are deposited by electron-beam evaporation after photo-lithography with AZ4210 polymer coated and baked  on the substrate. Graphite nanoflakes are exfoliated from single crystals with scotch tape onto polydimethylsiloxane (PDMS) blocks, and then transferred onto Au/Ti electrodes on the substrate, which allows the Au/Ti electrodes to become closer in lateral distance. IS and FGT nanoflakes are exfoliated and transferred onto the substrate by the same dry transfer method inside an Ar-filled glovebox  to prevent sample oxidation and degradation during fabrication. The completed device consists of a FGT/IS/graphite heterostructure in which a 12-nm-thick graphite (bottom layer) and a 10.5-nm-thick (13 layers) FGT (top layer) are spaced by a 50-nm-thick IS. The FGT is connected to the Au/Ti electrode through 5-nm-thick graphite. A large 20-nm-thick h-BN flake fully covers the FGT in order to minimize any chemical reaction or oxidation of FGT in air.The substrate is a 5 mm × 5 mm size Si wafer with a 300-nm-thick thermally oxidized SiOIn addition to PDMS, we use various types of polymer materials  for this dry transfer method, and as discussed in the main text, we always find the presence of an interfacial polymer layer. Typically, releasing the vdW material cleanly from the polymer requires a heating process. The difficulty lies in that the heating process should be limited when handling FGT; the ferromagnetic properties of FGT disappear after high-temperature (>80 °C) annealing. Additionally, applying chemical or etching methods, which alters the ferroelectric and ferromagnetic properties of the IS and FGT, respectively, should be avoided. Due to these restrictions, we are not able to prepare polymer-free interfaces with the dry transfer method. Nevertheless. the voltage effect on the FGT magnetic properties is consistently observed regardless of the polymer material used for the fabrication process  using Ga and Ar ions. The high-angle annular dark-field (HAADF) STEM images are acquired using monochromated and Cs-corrected TEM  equipped with a Gatan energy filter . The energy dispersive spectroscopy (EDS) spectra and maps are obtained from multiple EDS detector TEMs .VG is always applied through the graphite under IS while FGT is grounded  MOKE measurement system built by Neoark Corporation. The MOKE system has Kerr rotation detection sensitivity <0.1 mrad, and utilizes a polarized 408 nm diode laser. The measuring laser beam spot size (FWHM) is ~2 μm on the sample, but due to the Gaussian shape of the beam, signals can be detected >5 μm away from the center. Considering the small lateral size of the FGT/IS heterostructure (5–10 μm), the obtained Kerr rotation is the magnetic signal averaged over a majority of the heterostructure device. Yet, it is possible that some part of the Gaussian-shaped laser beam can drift outside of the heterostructure, i.e., where there is no FGT layer, in the presence of inevitable random sample drifts, which can result in some variation in the Kerr rotation signals. The MOKE data are averaged over 3–10 measurements in order to compensate, to some degree, for this measurement-to-measurement variation issue. The gate voltage ded Fig. .-1  and a cryogenically cooled Si CCD camera  at the Multidimensional Materials Research Center (MMRC) of Kyung Hee University. A 514.4-nm CW laser , whose bandwidth is further narrowed using Optigrate’s Bragg grating bandpass and notch filters for low energy Raman measurement, is attenuated with one of the selected neutral density (ND) filters and focused down to a 2 μm spot on the samples. The spectral resolution is 1 cm−1. The Raman peak positions are determined by fitting the measured data using the multiple-Voigt-function-model56. Multiple peaks are simultaneously fitted and the best-fit parameters  are found. The peak positions determined from the best-fit are plotted in Fig. Raman measurements are conducted at 300 and 70 K with a micro-Raman spectrometer with 1200 g mmVG is always applied through the graphite under IS while FGT is grounded  is used for the exchange-correlation functional with the Perdew-Burke-Ernzerhof (PBE) parametrization59. The projector augmented wave method60 is used with the energy cutoff of 600 eV and Γ-point centered 16×16×5 k-point grid. Spin–orbit coupling is included. The MAE is calculated using the force theorem62. Hole-doping is treated by reducing the total number of electrons with compensating uniform background charge. For each hole doping case, the atomic structures are obtained by relaxing the internal atomic coordinates with inclusion of the vdW interaction using the DFT-D2 method of Grimme63 where the experimental lattice constants with Fe-deficiency (corresponding to hole doping) is used. When there are no corresponding experimental values, the lattice constants are obtained by interpolating the known the reported experimental values. The electronic structures with in-plane strain are obtained by strained-bulk calculation where the in-plane lattice constants are changed according to the strain and the out-of-plane lattice constant is determined such that the unit-cell volume is conserved. With the fixed lattice constants, the internal-coordinate relaxation is performed.First-principles DFT calculations are performed using the Vienna ab-initio simulation package (VASP)Supplementary InformationPeer Review File


Stochastic optical reconstruction microscopy (STORM), a super-resolution microscopy technique based on single-molecule localizations, has become popular to characterize sub-diffraction limit targets. However, due to lengthy image acquisition, STORM recordings are prone to sample drift. Existing cross-correlation or fiducial marker-based algorithms allow correcting the drift within each channel, but misalignment between channels remains due to interchannel drift accumulating during sequential channel acquisition. This is a major drawback in multi-color STORM, a technique of utmost importance for the characterization of various biological interactions.We developed RegiSTORM, a software for reducing channel misalignment by accurately registering STORM channels utilizing fiducial markers in the sample. RegiSTORM identifies fiducials from the STORM localization data based on their non-blinking nature and uses them as landmarks for channel registration. We first demonstrated accurate registration on recordings of fiducials only, as evidenced by significantly reduced target registration error with all the tested channel combinations. Next, we validated the performance in a more practically relevant setup on cells multi-stained for tubulin. Finally, we showed that RegiSTORM successfully registers two-color STORM recordings of cargo-loaded lipid nanoparticles without fiducials, demonstrating the broader applicability of this software.https://github.com/oystein676/RegiSTORM.git and 10.5281/zenodo.5509861 (archived), and runs as a standalone executable (Windows) or via Python .The developed RegiSTORM software was demonstrated to be able to accurately register multiple STORM channels and is freely available as open-source (MIT license) at The online version contains supplementary material available at 10.1186/s12859-023-05320-1. Fluorescence microscopy is a widely utilized tool in cell and molecular biology, providing detailed structural information of specifically labeled target structures/molecules and their interactions. However, with conventional microscopic techniques the diffraction limit of light constrains the achievable resolution to roughly 200 nm. This major limitation has led to the development of super-resolution imaging methods such as Stochastic Optical Reconstruction Microscopy (STORM) , 2. In SInstead of visualizing only one target with fluorescence microscopy there is often a great interest in studying the interactions of multiple targets, necessitating multiple labels and multicolor imaging approaches. In diffraction-limited microscopy, this is straightforward as the image acquisition is quick, allowing multiple channels to be simply overlaid with no major (observable) error. In STORM, however, where the resolution is an order of magnitude higher than in diffraction-limited microscopy, various types of errors stemming from either the physics of light (e.g. chromatic aberration), image acquisition or image processing, are more frequently detected and need to be accounted for. Chromatic aberration and other imperfections in the optical imaging system are constant for a specific microscope setup and there are good tools available to easily correct these , 4. Due To enable multi-color imaging without sequential channel acquisition, different approaches have been presented. In a spectral demixing approach a dichroic-based emission splitter is used to separate simultaneously and with the same wavelength excited fluorophores based on their different emission spectra –9. RecenDespite being easily executable with minimal spectral crosstalk, sequential channel acquisition has the inherent challenge of proper channel registration, or alignment, which is highly crucial for the error-free evaluation of nanoscale interactions . In some cases it is possible to do the channel alignment manually based on the known biological interactions of the imaged targets (e.g. ring-center) . HoweverOver the recent years multiple single-molecule localization microscopy (SMLM) data processing softwares, some of which are open-access and available for e.g. ImageJ or Matlab platforms, have been developed and thoroughly evaluated and cross-compared , 20. SigIn this work we have developed an algorithm, which can identify fiducial markers in STORM data, and use them to accurately register multiple sequentially acquired channels. Importantly, the algorithm operates directly on localization data, and also outputs the corrected data in the form of localizations. Of note, chromatic aberration was corrected separately prior to registration using the Detection of Molecules (DoM) plugin in Fiji , and theIn this work we have developed an algorithm that utilizes fiducial markers to register multiple channels in STORM imaging to compensate for drift between the channel acquisitions. We have demonstrated the performance of the algorithm with several samples, including fiducial markers alone, multi-labeled tubulin in fixed cells and, using the cluster mode of the algorithm, cargo-loaded LNPs with no fiducials. These results are discussed in detail below. A schematic illustration of the RegiSTORM algorithm as part of the STORM imaging process is depicted in Fig. p = 1.1 × 10–27) for combination 1, from 362 ± 256 nm to 60 ± 36 nm  for combination 2, and from 496 ± 434 nm to 43 ± 24 nm & from 204 ± 86 nm to 49 ± 32 nm  for combination 3. These results demonstrate that the algorithm is capable of identifying the fiducials in the absence of other sample signals and successfully apply a rigid transformation to correct for the misalignment.To evaluate the performance of the algorithm we started from the simplest case, i.e. multi-color STORM images of fiducial markers alone, in the absence of any other signal which could complicate the detection of the fiducial markers. Using TetraSpeck™ fiducial markers we evaluated the following channel combinations: (1) 642 and 488 nm, (2) 642 and 561 nm and (3) 642, 561 and 488 nm. As the reference channels, we used 642 nm, 561 nm and 561 nm, respectively. Figure p = 5.2 × 10–10) for combination 1, from 593 ± 436 nm to 49 ± 32 nm  for combination 2, and from 177 ± 239 nm to 47 ± 46 nm & from 527 ± 181 nm to 65 ± 47 nm  for combination 3. The quality of the registration was further evaluated with Normalized Cross-Correlation (NCC), which also showed a clear overall improvement in the overlay as indicated by the increase in correlation coefficient values  were multi-labeled via immunostaining with a mixture of fluorophore-tagged secondary antibodies. Therefore, in case of successful registration, the microtubules in the different channels will overlap in the final reconstruction, making it possible to evaluate the performance of the algorithm under more realistic conditions. Importantly, the registration was still only based on the fiducials and not aided by the microtubule structures appearing in both channels. The same channel combinations (1) 642 and 488 nm, (2) 642 and 561 nm, 3) 642, 561 and 488 nm) and reference channels  were used as for the samples with fiducial markers only. Figure  642, 561 642 and p = 7.4 × 10–25)  nanoparticles which, depending on the labeling approach, may produce cluster-like signal signatures in STORM. We hypothesized that these signal clusters could be used as landmarks for registration in the absence of fiducial markers. Omitting fiducial markers from these types of samples can be beneficial for the STORM acquisition since matching the signal intensity from the relatively bright fiducial markers to that of structures within the samples, which often are much dimmer, can be challenging and easily hampers the image quality. To demonstrate the functionality of the cluster mode we imaged streptavidin-Alexa Fluor 647 loaded LNPs labeled with Alexa Fluor 488 lipid  and variance limit (VL). The MT helps to identify fiducial markers based on their stable emission across frames, while excluding isolated signals. However, when testing the algorithm on tubulin samples, we observed that the algorithm struggled to differentiate the fiducials from the microtubuli that also gave out frequent signals. Therefore, we introduced the VL, which defines a maximum allowed value for the variance of the number of nearby localizations across frames for a fiducial candidate. In the tubulin regions of the images we observed excessive blinking in the fluorescence signal, as expected, resulting in a high variance, whereas the fiducials are characterized by a constant stable signal and thus had a low variance. Therefore, by combining the MT, which finds relevant regions, and the VL, which distinguishes fiducials from densely labeled sample regions, it is possible to identify the fiducial marker localizations from the STORM data. The effect of adjusting MT and VL on the registration quality of two-color tubulin STORM images, as determined by TRE and NCC, is depicted as heat maps in Fig. To identify the fiducial markers from the STORM data the full frame set is processed by the algorithm by default. However, since we observed that there is some variation in the stability of the fiducial markers over the STORM acquisition : TRE and NCC. Due to user-dependency and humane inaccuracies the manual annotation is somewhat error-prone, which is why the absolute TRE values calculated here likely have some inaccuracy. However, we were still able to see a significant improvement in this metric, and our values (around 40–60 nm) are approaching the resolution limit of STORM microscopy (around 20 nm ). In terTo achieve high-quality registration using fiducial markers, the density and distribution of the fiducials in the sample, as well as inherent properties of the fiducial markers such as brightness and stability, play critical roles. Too low total count and a concentrated distribution of the fiducials, as well as positions in different focus levels when compared to the sample signal, can limit the algorithm's ability to identify them and calculate an accurate transformation matrix, particularly when it comes to the rotational component. All this can negatively impact the registration quality. On the other hand, if the fiducial density is too high or the fiducials are much brighter than the sample signal, there is a risk of masking the signal coming from the targets of interest, which can result in poor overall image quality. Although extensive evaluation and optimization of fiducial markers is beyond the scope of this work, these factors are good to keep in mind as potential error sources when conducting STORM channel registration utilizing fiducial markers.In this work we have developed a registration algorithm for sequentially acquired multi-color STORM images. The algorithm is capable of directly processing fluorophore localization data, as opposed to generated images, making it ideal for STORM. Its performance was initially demonstrated using only fiducial markers, illustrating that the algorithm can successfully identify the fiducials and apply a correcting transformation. Subsequently, the algorithm was shown to be functional in a more complex and experimentally relevant setup of multi-labeled microtubuli, suggesting the applicability of this tool in a wide range of experimental conditions in sequential multi-channel STORM imaging. Lastly, using the cluster mode of the algorithm for alignment, two-color STORM images of fluorescent cargo-loaded fluorescent LNPs were successfully registered in the absence of fiducial markers as references, which adds to the versatility of this tool. The algorithm is implemented in an open source software tool, RegiSTORM, providing a user-friendly GUI for easy selection of files, tuning parameters, conduction of the registration and saving the results. The software has been compiled into a Windows application so that users without experience in Python programming can easily use it. This tool has the potential to be instrumental in applying super-resolution microscopy to elucidate and accurately characterize a plethora of unknown nanoscale interactions  in cell biology and nanomedicine, such as extracellular vesicle composition and signaling, endosomal escape pathways, signaling pathways in general and localization of carrier and active molecules in drug delivery systems –42. The To develop and test the RegiSTORM software three sample types were prepared and imaged using STORM: fiducial markers only, cells immunostained for tubulin with fiducial markers and fluorescent lipid nanoparticles , 47 µg/mL catalase from bovine liver (C1345) and 10 mM cysteamine (pH adjusted to 8.0). All the components of the buffer were purchased from Sigma Aldrich . The μ-plate was further sealed with parafilm to decrease oxygen entry.Prior to imaging, the sample was soaked in imaging buffer with the following composition: Tris buffer , 10 wt% glucose, 0.5 mg/mL glucose oxidase from ®  and Micro-Manager open-source software [STORM imaging was conducted with a Nikon Ti Eclipse inverted microscope , with cube filters  and TIRF dichroic ZET405/488/561/640bs, and equipped with Cairn laser module  with 200 mW 488 nm, 150 mW 561 nm and 140 mW 642 nm lasers. A CFI SR Apo TIRF 100X oil objective (N.A. 1.49) was used with a 1.5X Optovar lense, thus giving a final magnification of 150X. The camera  had a pixel size of 13 µm. The image acquisition was controlled with MetaMorphsoftware . The regThe localization events and images from each channel were reconstructed with the ThunderSTORM plugin  in Fiji Manual annotation of the fiducial markers in both the fiducials only and tubulin STORM images was conducted with the ImageJ annotation tool by a single expert (M.O.). Briefly, by using the in-built multi-point tool the corresponding fiducials were clicked in all the images aiming to hit the very center of each dot. Thereafter the x,y coordinates of these selections were saved as a .txt file. Unclear targets or fiducial markers not observed in all the channels were omitted. In case of two-color tubulin samples the third channel  was used to guide in the annotation process. Manual annotation with the same approach was also conducted for the two-color LNP STORM images by roughly estimating the middle point of the LNPs. Non-loaded LNPs and signals from free cargo were omitted from the annotation. To improve the accuracy of the manual annotation, for each annotated point, we identified the localization coordinates in the STORM dataset closest to the manually annotated coordinates.RegiSTORM works by first identifying the fiducial markers, based on their non-blinking behaviour, in a reference channel and in one or more moving channel(s). After identifying the fiducials, it performs a rigid transformation to match the fiducial coordinates of the moving channel(s) to those of the reference channel. A detailed description of the registration algorithm is provided in the following subsections.Import STORM data (.csv format) reconstructed from the original image frames with a reconstruction software (e.g. ThunderSTORM ).Identify the frame with the highest number of localizations. All these localizations are initially considered as potential fiducials.r equaling the fiducial diameter (100 nm) from the coordinates of each potential fiducial. This is conducted using a KD-tree for quick nearest-neighbor lookup [Go through the remaining frames and search for localizations that are within a tolerance r lookup .c, apply two inclusion criteria, mean tolerance , i.e. the channels being transformed.Apply the Iterative Closest Point (ICP) algorithm , 34 to eApply the best-fit rigid transformations  estimated for the identified fiducials to all the localizations in the channels being corrected. A rigid transformation has a rotational and a translational component .Output the corrected localization lists as .csv-files.After identifying the fiducial markers the registration is performed according to the following steps:RegiSTORM has also an optional feature to remove the fiducial markers from the dataset for fiducial-free visualization and image analysis. This is accomplished by removing all the localizations within a distance of one fiducial diameter around the coordinates of the identified fiducials. The performance of this functionality is illustrated for Alexa Fluor 488/647 dual-colored tubulin samples in Additional file rc specified by the user is computed across all frames. The 25 localizations with the largest number of neighbours are retained as the identified clusters and used as landmarks for registration. The rigid alignment matrix transformation step remains the same. To demonstrate its feasibility we have used the cluster mode to register two-color STORM images of fluorescent cargo loaded labeled LNPs  Target Registration Error TRE, Eq.  which mei is the coordinate of the fiducial in the moving channel and Xj is the corresponding fiducial in the reference channel. For the NCC, N and M is the number of pixels in each dimension. I is the intensity at pixel i,j where m refers to the mean intensity and σ is the standard deviation of the intensity for the given image.For the TRE Xp values for the TRE calculations in the different datasets.A two-sided Wilcoxon signed rank test was used to evaluate statistical significance of differences in TRE before and after registration. A significance level of 0.05 was used. In the box plot visualizations of the quantitative data the box shows the data from lower to upper quartile, with median marked with a line, whereas the whiskers indicate the minimum and maximum. Automatically identified outliers are not shown in the plots. The number of fiducial markers/LNPs used for the TRE calculations is provided in Additional file RegiSTORM was developed using Python 3.8 and can be used either in a Python interpreter or as a Windows executable application. Dependencies include: Joblib, SciPy, SkLearn, OS, Pandas and Numpy. The GUI was implemented using the PySimpleGUI library, and the software was compiled into a Windows executable file using PyInstaller. The build was then compiled into an installable file using Inno Setup (JrSoftware) allowing the installation of the software on Windows computers.In the GUI, the user can build up a list of jobs, where each job is one set of registrations. When the user has defined all the required jobs and clicks ‘run’, the software will sequentially apply the algorithm to all the jobs in the task list (see documentation for the Github file).Additional file 1. Supplementary methods, supplementary figures S1-S4, supplementary tables S1-S5.


Department of Defense (DoD) health care planners want to stimulate a voluntary migration of prescription fills from military and community pharmacies to its mail-order pharmacy, a lower-cost dispensing option for the department. Beneficiary cost share for a 90-day supply of generic/ brand medication is $0/$0 at military (DoD) pharmacies, $3/$9 at the DoD mail-order pharmacy, and $9/$27 at network community pharmacies.To examine the pharmacy use patterns among the beneficiary population age 65 years or older, traditionally the heaviest users of the TRICARE DOD prescription drug benefit, to identify factors that are associated with beneficiary use of pharmacy setting(s).Outpatient prescription fill records were examined for TRICARE beneficiaries age 65 years or older  residing in North Carolina, Texas, and California for dates of service from December 1, 2004 through February 28, 2005. Binary logistic regression models were run for each type  and number of pharmacy settings used by beneficiary gender, age group, catchment area status (located either within or outside a 40-mile radius of each military pharmacy), state, and number of medications obtained . The mean number of medications per beneficiary and cost per medication were tabulated for each type and number of settings used.In the 3-month period from December 1, 2004 through February 28, 2005, beneficiary use of military, community, and mail-order pharmacies was 45.4%, 67.6%, and 22.1%, respectively. About 67% of the study population used 1 setting exclusively and 2.4% used all 3 settings. Noncatchment residents were significantly less likely  to use a military pharmacy exclusively and significantly more likely to use a community pharmacy  or the mail-order pharmacy  exclusively than were catchment residents. Beneficiaries taking 10 or more medications were more likely  to use multiple settings than were those who obtained 3 or fewer medications. Single-setting users obtained a median of 4 (interquartile range [IQ]) 2-7) medications with a median copayment of $7.00 (IQ $0-$13.19) per medication. Those who used all 3 settings obtained a median of 9 (IQ 7-12) medications with a median copayment of $4.33 (IQ $3.00-$6.00) per medication. Among beneficiaries who obtained 6 or more unique medications during the 90-day study period, approximately 25% used the mail-order pharmacy to obtain 1 or more prescription fills.A significant portion of the study population did not use the mail-order pharmacy despite the financial incentive to use mail-order rather than community pharmacies. Relatively small financial incentives alone may be inadequate for promoting a switch to the mail-order option among those beneficiaries not already using it in a pharmacy benefit plan with low copayments. Larger monetary and other incentives may be necessary to achieve the desired transfer of prescriptions fills to the mail-order pharmacy and the associated reduction in military pharmacy workload.


With high recurrence and metastatic rates, triple-negative breast cancer (TNBC) has few therapy choices. The innate immune stimulator of interferon genes protein (STING) pathway has emerged as a critical foundation for improving anticancer immunotherapy. Although 2’,3’-cGAMP has been shown to have therapeutic potential as a STING agonist in subcutaneous solid tumour treatments in mice, the effect of cGAMP in metastatic malignancies has received less attention.Bioluminescence imaging technology was applied to monitor TNBC tumour cell metastasis in living mice. Serum biochemical test and blood routine examination of mice were used to demonstrate cGAMP administration had no toxicity. The activation of DCs and CD8+ T cells was demonstrated by flow cytometry. The pharmacological mechanism of cGAMP for suppressing breast tumour metastasis was also explored.cGAMP treatment substantially suppressed tumour development and metastasis without adverse effects. cGAMP activated the cGAS-STING-IRF3 pathway, which modified the tumour immune milieu to reverse the Epithelial-Mesenchymal Transition (EMT) and PI3K/AKT pathways and prevent tumour metastasis. It was postulated and proven that cGAMP had a pharmacological mechanism for reducing breast tumour metastasis.The findings suggest that cGAMP could be useful in the immunotherapy of immune-insensitive metastatic breast cancer. Breast cancer (BC) is the most common malignant cancer in females worldwide, and metastasis is the leading cause of death . Patient (I-IFN) . cGAS is (I-IFN) . As an a (I-IFN) , which i (I-IFN) . At the  (I-IFN) . It larg (I-IFN) . The inn2.2.1.cGAMP was produced in our laboratory as previously described ,16. The 2.2.via CO2 inhalation and cervical vertebra dislocation at the end of the trial. Respiratory and cardiac arrest, as well as a lack of a righting response, verified the animal’s death.The Institutional Animal Care and Use Committee at Fudan University (Shanghai) authorized all operations in the study in accordance with the Animal Experimentation Ethics Guidelines. The Beijing Vital River Laboratory Animal Technology Co. Ltd. provided us with 18 female seven-week-old specific pathogen-free (SPF) BALB/c mice weighing 18–22 g . The mice were then kept in a specific pathogen-free (SPF) facility  with a 12/12-h light/dark cycle and free access to normal laboratory animal feed and tap water. During the investigation, no mice were sacrificed. The animals were killed 2.3.Mouse cGAS protein and cGAMP were made following ,16. The 2.4.2, 4T1-Luc cells transfected with luciferase were grown in RPMI-1640 media  with 10% heat-inactivated FBS  and 1% penicillin/streptomycin. 4T1-Luc cells were trypsinized and washed before resuspended in RPMI-1640 media without foetal bovine serum and antibiotics at 106 cells/mL. 200 μL cells were injected intravenously into the tail vein of mice. The tumour-bearing mice were randomly separated into two groups one day following injection. One group served as a control, while the other received cGAMP (20 mg/kg) intraperitoneally daily for a month. Full blood was obtained at the end of the study for routine blood testing. Mouse blood samples were extracted from the ophthalmic vein after anaesthesia with a mixture of oxygen and isoflurane, and serum was recovered by centrifuging at 300 g for 30 min for the serum biochemical test.In a humidified 37 °C incubator with 5% CO2.5.in vivo. In vivo Biophotonic imaging was used to identify tumour cell spread and proliferation. Mice were weighed and intraperitoneally treated with 150 mg/kg luciferin. After 9 min of luciferin treatment, the animals were pre-anesthetized using an oxygen-isoflurane mixed gas (1%–3%). At 12 min following luciferin administration, the animals were placed into the imaging chamber for bioluminescence measurement assessment using a Xenogen IVIS Lumina XRMS Series III live animal bioluminescence imaging system . On the last day, mice were sacrificed, then their hind limbs and organs were imaged and removed within 10 min.We created 4T1-Luc cell lines to express firefly luciferase stably, which allowed us to track and quantify cells 2.6.+ T cells with CD8α and CD3 antibodies and stained CD4+ T cells utilizing CD4 and CD3 antibodies. Neutrophils were labelled by CD45+CD11b+Ly6G+. M2-type tumour-associated macrophages (M2-TAM) were labelled by CD45+CD11b+F4/80+CD206+. We labelled DCs through CD11c monoclonal antibodies, which we stained with anti-mouse CD80, CD86, MHC II and CD40.We removed spleens from mice and isolated spleen cells at the termination of study . At the 2.7.Mice blood was collected and centrifuged at 1000 rpm for 10 min to extract serum for the test. In presence of protease inhibitors, lung tissues from three groups of uniform weight were mechanically homogenized. Supernatant homogenates were produced after centrifugation and kept at −80 °C for further use. The concentration of cytokines in the serum and lung tissues was determined using mice ELISA kits and the manufactures’ instructions.2.8.Lung tissues were fixed in 4% paraformaldehyde for at least 24h. Lung tissues fixed in paraffin were sliced into slices (5 μm), and then slices were deparaffinized in xylene and rehydrated in 100%, 95%, 85% and 75% ethanol. Haematoxylin and eosin were used to stain them. The slices were discovered using a light microscope 2.9.The lung tissue slices were prepared according the description in 2.8. After blocking, the slices were stained with the primary antibody of p-PI3K, p-AKT, E-cadherin or Vimentin at 4 °C. The secondary antibody and DAPI were stained in dark. The fluorescence photographs were obtained using a fluorescence microscope .2.10.p value <.05 was regarded as a statistical significance.Each group had ≥ 6 mice, while all tests were repeated in triplicates. The date was shown as mean ± standard error (SEM). Statistical analyses were conducted with one-way ANOVA by GraphPad Prism  and 3.3.1.In vivo imaging technologies were used to investigate particular biological and cellular processes in living animals using the reporter gene methodology [The mass spectrum data regarding successful cGAMP synthesis are inferred in hodology . When thhodology .4T1-Luc cells in exponential phase of proliferation were collected to inoculate into female BALB/c mice by tail vein. Daily intraperitoneal administration of 20 mg/kg cGAMP was started on the two days after tumour inoculation. On the 4 days, 11 days, 19 days, 26 days and 32 days, mice were injected with luciferin, and the tumour proliferation and metastasis in mice were monitored by animal bioluminescence imaging after anaesthesia .Tumour cells metastasized through blood circulation and formed new tumours in thoracoabdominal region  and back3.2.It was obviously found that the weight of mice bearing tumours decremented quickly since 20 days after inoculation, but the other groups of mice grew normally . The wei3.3.TNBC has a high rate of metastasis and tends to metastasize to lung tissue with some capillaries. The lung tissues of sacrificed mice were obtained and fixed in 4% paraformaldehyde for at least one day. Pulmonary metastasis nodules were visualized after morphologic fixation, which were counted manually . The ave3.4.in vivo, playing critical roles in the regulation of innate and adaptive immunity [in vitro [+ cells were gated to examine the expressions of CD40, CD86, CD80 and MHC II. cGAMP treatment dramatically increased the expression of these four DC markers  were antigen-presenting cells (APCs) immunity . Surfacein vitro . In the  markers , indicat T cells . Becausent group .Tumour associated macrophage was expressed highly amongst most cancer patients, who suffered from promoted tumour proliferation and metastasis . In the +CD11b+Ly6G+ cells, were the major components of non-specific immunity. They could not only resist microorganisms and pathogens, but also function importantly in tissue repair [+ T cell activation to facilitate metastasis of many cancers, especially BC [Granulocytic MDSCs, defined as CD45e repair . Howevere repair . What’s ially BC . In BC pially BC ,34. The 3.5.+CD8+ T cells that limit tumour development [via the tumour necrosis factor-related apoptosis-inducing ligand (TRAIL) pathway [ELISA was used to detect antitumour cytokine expression in serum. In comparison to tumour-bearing animals, cGAMP treatment stimulated the production of immune cytokines with anticancer potential, such as IFN-β and IFN-γ . Endogenelopment ,38. Incr pathway .+ T cells being known as antigen stimulation response [+ T cells expression by flow cytometry test. Purified IL-2 infusion significantly increased lymphocyte persistence and anticancer impact in mice [Tumour necrosis factor-α (TNF-α), mainly generated by activated mononuclear macrophages and other cells, was a cytokine capable of causing haemorrhagic necrosis of tumour tissue cells . The up-response , which w in mice ,44. Rose in mice .+ T cells, hence promoting tumour development and metastasis [+ T cell suppressor type, followed by the establishment of breast tumour metastasis in distant organs. Certain cytokines can be modulated by cGAMP treatment to exert anti-tumour action and prevent tumour spread.On the contrary, the current study revealed that elevated serum levels of IL-10 and IL-17A in tumour-bearing mice were strongly associated with BC metastasis, and cGAMP treatment could counteract the effect . Interletastasis . The fin3.6.Certain chemokine receptors on tumour cell surfaces were involved in multiple steps of tumour genesis and metastasis . CXCR4 wIn our experiments, the cytokines including TGF-β and CXCL12 in serum and lung tissues were measured by ELISA to analyse the impact on BC metastasis. TGF-β, highly generated by tumour cells, and some suppressive immune cells, could induce tumour cells metastasis by the EMT  process . As a reMSCs  were pluripotent stem cells that enable to produce several chemokines, such as CCL5 and CXCL12 . CXCL12 Furthermore, the EMT process has been extensively researched as one of the causes of tumour spread. The EMT process, which is driven by essential transcription factors, allows epithelioid tumour cells to adopt a mesenchymal character, increasing their propensity to spread. E-cadherin (E-cad) was found in high concentrations on epithelioid cells, whereas Snail, Twist and Vimentin were found in high concentrations on stromal cells ,59. EMT CXCR4 binding to the ligand SDF-1 activated the phosphoinositide 3-kinase/protein kinase B (PI3k/Akt) signalling pathway , which h+ T cell proliferation and produced IFN-γ. cGAMP could reshape tumour microenvironment, reverse the immune-suppressive microenvironment caused by M2-TAM and reduce the polarization of M2-TAM, thus decreased the expression of TGF-β secreted by M2-TAM, inhibiting the EMT process and tumour metastasis. The reduction of TGF-β, which reduced CXCR4 receptor expressions on the tumour cell surfaces and weakened the intracellular PI3K/AKT pathway activation, further impeded tumour development and metastasis  under tumour microenvironment influence. The number of neutrophils and TAMs in patients is connected to tumour progression and patient survival, and cancer cells can hijack the host’s protective immune system, promoting further growth and metastasis [In our current investigation, we tested the antitumour effect and toxicity of cGAMP by systematic administration in TNBC. The findings revealed that cGAMP activated innate and cross-primed adaptive immunity, increased and enhanced antigen-presenting activity of DCs, and activated CD8tastasis . Upon actastasis . Currenttastasis ,74. cGAMWe also explored the mechanisms for tumour metastasis suppression of cGAMP in detail. Increasing evidence suggested that many tumour progression steps were influenced by the tumour microenvironment. Cancer cells were impacted not only by each other, but also by extracellular matrix (ECM) and other microenvironmental cells such as endothelial cells, fibroblasts and inflammatory cells .+ tumour cells tend to metastasize to organs that express CXCL12 via blood vessels [in vivo, poor tissue permeability and systemic toxicity [CXCL12/CXCR4 signal transduction not only promotes dysplasia and stress of tumour tissues, inducing physical barrier for therapeutic agents and T cell penetration, but also functions importantly to promote tumour cell migration, proliferation and invasions ,77. CXCR vessels . Pharmac vessels . Some smtoxicity .STING is expressed ubiquitously in cells, and cytosolic nucleotides from pathogens or damaged cells could activate STING. Particularly, it is showcased that intratumoural injection of synthetic cyclic dinucleotides (CDN) could elicit rapidly the IFN-β expression by immune cells in tumours and generate anti-tumour specific CD8+ T cells to inhibit tumours development . TGF-β iWhile immunotherapy is extremely promising, one major difficulty is that many malignancies continue to be resistant to existing cancer treatment. This study demonstrated the exceptional efficacy of cGAMP alone on TNBC treatments, despite the fact that most other medications showed no response. T cell response and antitumour memory were evoked by cGAMP, which inhibited the growth of metastatic cancers in organs. The findings revealed that cGAMP might achieve an effective antitumour immune response in cancers that had limited or no response to immune checkpoint targeted therapies. As a result, cGAMP might represent a unique potential TNBC immunotherapy.5.via the cGAS-STING-IRF3 pathway, thereby triggering the generation of cytokines and immune cells to destroy tumour cells. The following mechanism was: cGAMP stimulated innate and adaptive immunity, changed the tumour immune milieu, down-regulated the expression of M2-TAM and TGF-β and impaired the combining capacity of CXCR4 and CXCL12. The tumour metastasis-facilitating pathways, including the EMT process and the PI3K/AKT pathway, were further suppressed, reducing tumour metastasis in particular organs. Based on these advantages and our findings, cGAMP might be developed as a potential immune inhibitor for the treatment of metastatic breast cancer. The innate immune and adaptive immune have complicated synergistic effects on regulating tumour metastasis. However, the mechanism of STING agonist administration that drives antitumour immune responses to suppress breast tumour metastasis remains unknown. In this study, we evaluated the antitumour efficacy of cGAMP in metastatic BC. More importantly, based upon the immune cytokine expressions in mice serum and lung tissues, the immune cells expression in spleens and the related protein regulations in PI3K/AKT signalling pathway and EMT signalling pathways, the pharmacological mechanism of cGAMP to suppress BC pulmonary metastasis was further studied.This study found that cGAMP treatment can decrease breast tumour metastasis and, in particular, diminish pulmonary metastasis, increasing mice’s living conditions and survival rate. As the second message, cGAMP, might activate innate and adaptive immunity in mice


Bland–Altman 95% limits of agreement between methods was − 212 to 180 ml. The smart bottle provided accurate measurements of fluid intake during exercise in real-world field conditions on a group level and within limits of agreement of − 212 to 180 ml  on an individual level.Rehydration is important for athlete performance and recovery. However, it can be challenging to follow appropriate fluid replacement practices due in part to difficulties in tracking fluid intake in real time. The purpose of this study was to determine the accuracy of a smart bottle in measuring fluid intake during exercise. Thirty male American football athletes drank from bottles equipped with a smart cap during outdoor pre-season practices . The cap technology included optical sensors, microprocessors, batteries, and wireless connectivity that transmitted fluid volume data to a smartphone application in real-time. Reference measurements of fluid intake from the smart bottle were determined by gravimetry followed by conversion to volume using the density of the fluid consumed. There was no significant mean difference in fluid intake between the smart bottle and reference method (1220 ± 371 ml vs. 1236 ± 389 ml, p = 0.39 paired  Several studies have assessed best practice methodologies and new technologies to conduct sweat testing to help inform athletes’ individualized fluid replacement needs4. However, the other important aspect of optimizing hydration status during activity is ensuring that fluid intake recommendations are followed by athletes. Observational studies have shown that some athletes accrue significant dehydration despite having access to fluid5, while others may overdrink relative to sweat losses during exercise7.Current consensus recommends that personalized hydration practices should be followed by athletes to attenuate the adverse effects of fluid-electrolyte imbalances on health and performance8. A possible approach to improve fluid intake tracking by athletes and/or their sports practitioners in real time is through the use of smart bottles, which have recently become commercially available. Previous studies have assessed various smart bottle technologies and reported their accuracy to be within 2–24% of reference measurements for 24-h fluid intake10. To date, most research with smart bottles has been related to their potential utility as a behavioral aid to improve hydration in recurrent kidney stone patients, as difficulty remembering to drink is a common barrier to sufficient fluid intake in this population13. By contrast, no studies have assessed the accuracy of a smart bottle technology when used by athletes in the context of real-world training conditions. If valid, smart bottle technology may also aid adherence to fluid intake recommendations in athletes.One of the challenges to following appropriate fluid replacement practices may be related to difficulties in knowing how much volume an athlete has ingested14; as the combination of warm environmental conditions and intense training can lead to substantial fluid loss through sweating17. For example, in one study with professional players of the National Football League (NFL) (124 ± 25 kg) sweating rate was 2.3 ± 0.4 L/h, which led to a 2.3 ± 1.1% body mass deficit over the course of a 2.2 h practice18. However, there is wide variation in sweat losses among studies, depending upon player size, environmental conditions, equipment worn, and training intensity, among other factors19. Normative data suggest that the range in sweating rate in American football is ~ 0.5 to 4 L/h15. Accordingly, a wide variation in fluid balance has also been observed in American football players14, with one study reporting a range of 0.0–2.8% change in body mass among NFL lineman and backs20.American football players are among the more susceptible athletes to body fluid deficits, especially during summer pre-season trainingSmart bottle technology may be a tool to help athletes and/or their sport practitioners better gauge fluid intake during exercise to prevent significant under- or overdrinking. However, the accuracy of smart bottle technology in measuring fluid intake during exercise in real-world field conditions is unknown. Therefore, the purpose of this study was to compare fluid intake measured with a smart bottle to standard reference fluid intake measurements during American football pre-season practice sessions.Thirty male American football athletes participated in this study. All participants were members of the same post-graduate team based at the IMG Academy in Bradenton, Florida, USA. This study  was approved by the Sterling Institutional Review Board (sterlingirb.com) and has therefore been performed in accordance with the ethical standards in the Declaration of Helsinki. Each participant and his parent or guardian (for subjects under 18 years) were informed of the experimental procedures and associated risks before providing written informed consent or written informed assent (for subjects under 18 years).Testing took place over the course of three pre-season outdoor practices held in the early mornings during 1 week in August. The practices were led by team coaches and consisted of a range of activities including dynamic stretching, position-specific drills, and live scrimmaging. The intensity and duration (75–130 min) of the practices, as well as the breaks in activity were not influenced by the investigators. Players wore helmets, shoulder pads, jersey top, shorts, and cleats during practices. The temperature and relative humidity during practice were measured with a Kestrel 5400 (Nielsen-Kellerman Co.) positioned on the sideline. Each of the 30 players participated in the study during one of the three practices (i.e. n = 10 per practice). One player did not practice because of injury but still participated in the study by drinking ad libitum on the sideline.x Bottle, described in more detail below). The athletes were allowed to drink during substitutions as well as scheduled drink breaks for a total of ~ 3–6 opportunities to drink per practice. Reference measurements of fluid intake from the smart bottle were determined by gravimetry (change in bottle mass) using a compact digital bench scale  followed by conversion to volume using the density of the fluid consumed (6% carbohydrate-electrolyte solution). Bottle measurements using both the smart bottle technology and the reference method were obtained before practice, before/after refills during practice (as needed), and after practice to determine total fluid intake for each participant. The bottles sat resting on a flat surface (i.e. table) during the measurements. Fluid volume measurements were conducted in triplicate at each time point to assess reliability. The first value of the triplicate measurements at each time point was used in the calculation for fluid intake. Bottles were stored in ice chests on the sideline and players drank from their individually labeled bottles during breaks in practice.During practice, players drank ad libitum from 0.9 L-squeeze bottles equipped with a smart cap . Players wore compression shorts only and were asked to towel dry prior to stepping on the scale. Post-exercise fluid balance was calculated as the difference between pre- and post-practice body mass. Whole body sweating rate was calculated as the difference between pre- and post-practice body mass adjusted for fluid consumed (based on reference measurement of fluid intake). No food was consumed and there was no urine/stool loss between pre- and post-practice body mass measurements. Three players did not weigh in before practice and one player did not weigh out after practice. Therefore, the sample size was n = 26 for fluid balance and WBSR data. All data were recorded on paper by study investigators. After the training sessions, the lead author entered data into a digital spreadsheet and a coauthor checked the accuracy of the inputs.The Smart Bottle used in this study was a 0.9 L plastic squeeze bottle with technology integrated into the cap—including sensors, microprocessors, batteries, and wireless connectivity—that detects the level of liquid inside the bottle and transfers the fluid volume data to a smartphone application. The sensors in the cap measure the liquid level inside the bottle via a laser optical method based on the Time of Flight (ToF) principle. ToF is the time it takes emitted photons to travel from the cap, through the air gap below the cap, and bounce back (reflect) from the level of the liquid (the target). The ranging distance is calculated by the time difference between the emission and the reception of the photons, providing the actual distance of the target in millimeters. The distance between the cap and the top of the liquid is then correlated to volume in milliliters based on the bottle’s geometry. The Smart Bottle needs to be resting on a flat surface within 10 m of the smartphone to make fluid volume measurements and the data are transferred to the application 30–60 s after measurement initiation. To collect fluid volume data from multiple bottles a separate smartphone application/device needs to be paired to each bottle.t tests were used to evaluate the difference in fluid intake between methods. Bland–Altman plots for predicted versus measured fluid intake were used to illustrate results by individual participants and 95% limits of agreement (LOA) were set around the mean difference (line of bias). A correlation calculation between the outcomes of the y-axis (difference between smart bottle and reference method) and x-axis (average of smart bottle and reference method) of the Bland–Altman plot was conducted to determine if there was a significant difference in over or under-estimations when taking into account the total volume consumed (low vs high drinkers). An orthogonal (Deming) regression was conducted, whereby the slope and intercept of the regression line and line of identity of the scatterplot were compared, to determine the accuracy of the smart bottle in measuring fluid intake. Shapiro–Wilk tests were used to assess the normality of the residuals. For practical context, fluid intake prediction error was also expressed as a percentage of body mass for each player. Pre-practice body mass was used for this calculation except for n = 3 players who did not weigh in before practice, in which case their post-practice body mass was used. The significance level for all statistical tests was set at alpha = 0.05.Analyses were carried out using XLSTAT , Minitab 19 Statistical Software (Minitab Inc.), and NCSS 12 Statistical Software . Values are presented as mean ± SD. Scatterplots and Pearson correlation coefficients were obtained to assess the relation between the smart bottle and reference methods for fluid intake. Paired The participants age and body mass were 18 ± 1 years and 92.4 ± 20.4 kg, respectively. Practice duration was 110 ± 30 min and the conditions on the field were 29.3 ± 3.0 °C and 75 ± 11% relative humidity. The players drank 1236 ± 389 ml of fluid during practice and their whole body sweat loss was 1.95 ± 0.82 L. Overall fluid balance at the end of practice was − 0.64 ± 0.73%. A breakdown of the descriptive data by practice day are shown in Table When using the smart cap to measure bottle fluid volume the mean coefficient of variation (CV) across all 110 measurement time points  was 18%. The absolute variation among the triplicate measurements was 38 ± 40 ml (range: 0–234 ml) with the smart cap. The mean CV using the Ohaus scale to measure fluid mass was 0.1% and varied by no more than ± 2 g among triplicate measurements.t test). The mean difference between methods expressed as a percentage was − 0.6 ± 7.5%. The 95% confidence interval (CI) for the percentage mean difference was − 3.4% (lower bound) to 2.2% (upper bound)  Fig. B. FigureAs shown in the scatterplot in Fig. For practical context the fluid intake measurement error of the smart bottle was expressed as a percentage of the athlete’s body mass Fig. . Based o21.This study determined the accuracy of a smart bottle in measuring ad libitum fluid intake by American football athletes during pre-season outdoor training sessions. The smart bottle used in this study was a squeeze bottle with optical sensors integrated into the cap that detect the level of liquid inside the bottle and Bluetooth connectivity to transfer the fluid volume data to a smartphone application. The main finding was that there was no significant mean difference in total fluid intake between the smart bottle and reference method. Further, the slope and intercept of the regression line describing the smart bottle versus the reference method were not different from one and zero, respectively. Bland–Altman 95% Limits of Agreement between methods was − 212 to 180 ml, which translates to approximately ± 15% of the players’ overall fluid intake. Therefore, the smart bottle is a valid and practical tool that provides fluid intake measurements within ± 15% of standard reference methods during exercise in real-world field conditions. When expressed as a percentage of the athletes’ body mass, this measurement error translates to a 0.31% overestimation to 0.17% underestimation in overall fluid balance. When combined with sweat testing to help inform athletes’ individualized fluid replacement needs, a smart bottle could help close the loop on real-time hydration. By having access to the fluid volume data through the smartphone application, the individual athlete or their sports practitioner could monitor fluid intake and compare it against pre-determined fluid intake goals that were based on sweat loss10 tested the accuracy of four commercially available smart bottles (n = 1 each) during a controlled phase of 50 sips (known volumes poured out by hand) and a free-living phase of 50 sips . The cumulative mean percentage error compared with ground truth weight-based measurements after 100 total sips ranged from ~ 2 to 24% across the four bottles tested. The capacitive sensor-based bottles had a lower mean error (1.9% and 2.1%) than the weight sensor-based bottles (− 13.3% and − 24.1%)10. In another study9, the accuracy of a smart bottle with a capacitive touch sensing technology was tested over a two-week period in a free-living setting with eight participants. Daily smart bottle measurements of fluid volume were compared against the participants’ measurements made by hand using a measuring cup. The overall mean difference between hand and smart bottle measurements was 0.0%, with a 95% confidence interval of − 3% to 3%9. Similarly, the mean fluid volume error in the present study was − 0.6 ± 7.5% for the 30 smart bottles tested, with a 95% confidence interval of − 3.4% to 2.2%.Previous studies have assessed various smart bottle technologies, including capacitive sensors extending from the bottle cap or weight sensors mounted on the bottle base. Cohen et al.22 compared observed fluid intake versus estimated fluid intake via the Food and Fluid Exercise Questionnaire (FFEQ) in 58 recreational endurance athletes competing in four different running events and one cross duathlon in the Netherlands. The FFEQ included questions on food and fluid intake during exercise as well as photographs for different serving sizes of beverages to facilitate the reporting of fluids. In this study the median observed fluid intake was 262 ml/h compared with 268 ml/h estimated from the FFEQ. Based on the Bland–Altman analysis there was a non-significant mean bias of 18 ± 106 ml/h and 95% LOA of − 198 to 225 ml/h22, equating approximately to a possible − 76% to 86% measurement error on an individual level. By comparison, in the present study the mean reference method fluid intake was 1236 ± 389 ml compared with 1220 ± 371 ml estimated from the smart bottle, with a 95% LOA of − 198 to 225 ml . Thus, while a questionnaire may accurately estimate fluid intake on a group level during competitions in recreational athletes, there seems to be potential for larger measurement error on an individual level compared with smart bottle technologies. However, a study using all three methods of assessing fluid intake  would be needed to make direct comparisons.Questionnaires have also been used to estimate fluid intake during exercise. For example, Wardenaar et al.This study builds upon previous literature by reporting the accuracy of a novel optical sensor-based smart bottle when used by athletes in the context of real-world training conditions. The testing took place in ecologically valid conditions, whereby athletes were able to drink ad libitum and use the smart bottles at free-will during breaks in practice. In addition, the bottles experienced large temperature variations, from storage in ice chests during transport and on the sideline to the warm/humid outside air when being used by athletes. Furthermore, for practical interpretation of results the fluid intake measurement error of the smart bottle was expressed as a percentage of athlete body mass. Based on these results overall fluid balance would be altered by + 0.31% to − 0.17% during practice due to the difference between smart bottle and actual fluid intake volumes, which is likely of practical and clinical insignificance.15, sweating rates (0.47–2.51 L/h) and total sweat losses (0.77–3.72 L) varied considerably among American football players, with some experiencing significant fluid losses as a result of the high intensity practice and warm/humid conditions. Fluid balance also varied substantially among athletes; ranging from 2.35% loss to 0.47% gain during the practice sessions, which is similar to previous observations in American football20.In agreement with previous observations11. Whereas another study found the use of a smart water bottle did not further augment urine output in kidney stone patients beyond counseling alone13. Future research is needed to determine the utility of smart bottle technology in improving hydration practices and fluid balance during physical activity or sports practices/competition. In addition, future research is needed to determine the accuracy of the smart bottle at various beverage temperatures (e.g. ranging from warm to cold).A limitation of the present study was that each player was tested only once to make within subject comparisons between the smart bottle and reference method for measuring fluid intake. It would be useful in future research to assess within person (day-to-day) variation of the measurement as well as compare ad libitum fluid intake behavior between the smart bottle and standard squeeze bottle. Previous research has reported that everyday use of a smart bottle improved hydration (24-h urine volume) in stone formers by helping them remember to drink waterIn summary, this study tested the accuracy of a smart squeeze bottle that measures fluid intake in real time via cap-integrated optical sensors. There was no significant mean difference in total fluid intake between the smart bottle and reference method when tested with American football players during pre-season training sessions. Bland–Altman 95% limits of agreement between methods was − 212 to 180 ml. Therefore, the smart bottle provided accurate measurements of fluid intake during exercise in real-world field conditions on a group level and within limits of agreement of approximately ± 15% of overall fluid intake on an individual level. This technology represents a valid and practical tool to measure fluid intake in real-time, which may help facilitate adherence to personalized hydration strategies during exercise.