These spectra were then compared with those calculated by using density functional theory. For all cluster sizes, calculated structures adopting asymmetric solvation to one Zn atom in the dimer were found to lie lower in energy than structures adopting symmetric solvation to both Zn atoms. Combining experiment and theory, the spectra show that water molecules preferentially bind to one Zn atom, adopting water binding motifs similar to the Zn+(H2O)n complexes studied previously. A lower coordination number of 2 was observed for Zn2+(H2O)3, evident from the highly red-shifted band in the hydrogen bonding region. Photodissociation leading to loss of a neutral Zn atom was observed only for n = 3, attributed to a particularly low calculated Zn binding energy for this cluster size.Investigating metal-ion solvation—in particular, the fundamental binding interactions—enhances the understanding of many processes, including hydrogen production via catalysis at metal centers and metal corrosion. Infrared spectra of the hydrated zinc dimer (Zn Many chemical and spectroscopic properties of zinc are more similar to those of the alkaline earth metals when compared to other transition metals [Metal–metal bonds have received much interest over the years; however, homonuclear metal bonds have received particular attention. There have been numerous experimental and theoretical studies on homonuclear transition metal dimers, including Zn bonding ,23,24,25n metals .2, is only bound by weak van der Waals interactions [2− anion is considered to be unstable towards autodetachment [As Zn has a closed electronic configuration, the neutral dimer, Znractions . Whereastachment . The firtachment ,27. Andrtachment . Later, tachment . 2+ cation in the gas phase and discussed an ion-induced dipole bonding interaction between the two Zn atoms vs. covalent bonding with a bond order of one half [2+ displays rapid displacement of Zn, forming Zn+–molecule complexes, consistent with a weak binding interaction in Zn2+ [2+, reporting a bond length of 2.60 Å and a value for the dissociation energy D0(Zn+–Zn) of 1.73 eV. In 2019, Tarento et al. conducted a theoretical study on charge localization in small group 12 clusters and found that Znn+ (2 ≤ n ≤ 7) clusters have a regular, compact shape, with charge delocalized over the whole cluster [2Ln+  was performed in 2005 by Wu et al. observing that the primary fragmentation routes are either the loss of a neutral Zn atom or loss of a single ligand molecule [In 1988, Buckner et al. investigated the Znone half . Further in Zn2+ . In 2003 in Zn2+ . Their r cluster . A studymolecule ,31.2+(H2O)n. Studying hydrated metal ions in the gas phase provides the opportunity to investigate solvation at a molecular level and to study various chemical processes such as hydrogen production via catalysis at metal centers [+(H2O)n with up to 35 water molecules, [+, which was previously established by Duncan and co-workers for n ≤ 4 [2+. Do water molecules bind symmetrically to both Zn atoms, or do they preferentially bind to one Zn atom, and at which cluster sizes are different binding sites observed? By size-selecting each complex, a detailed investigation answering such questions can be carried out. To the best of our knowledge, this is the first experimental IRMPD study on hydrated metal dimers. Going to large cluster sizes up to 20 water molecules, the evolution of infrared spectra with increasing cluster size is a first step towards understanding metal dimer solvation.In this work we present an infrared spectroscopic study of hydrated zinc dimer ions, Zn centers  and corr centers  in a wel centers ,49,50,51 centers ,58,59,60 centers ,67,68,69lecules,  where weor n ≤ 4 . Here weInfrared spectra of size-selected clusters were recorded via action spectroscopy, Reaction (1):n = 3, a competing fragmentation channel was observed; photodissociation of the neutral zinc atom is represented by Reaction (2):However, for 2O) was also observed for n = 4, most likely in a sequential reaction, initial H2O evaporation followed by Zn loss upon absorption of further IR photons. 2+(H2O)n; n = 1–8, 10, 16, and 20), assuming a one-photon process for the calculated cross-sections. At least for the larger clusters, this is realistic, since the photon energy is close to the typical binding energy of a water molecule in water clusters—0.45 eV [n = 1, presents one band centered at 3580 cm−1. For n = 2, the experimental spectrum is different to that of monatomic Zn+(H2O)2, investigated previously [−1, along with an intense narrow band at 3590 cm−1, presenting a shoulder at 3680 cm−1. The n = 3 complex presents two different photodissociation channels: (i) loss of intact water molecules and (ii) loss of a neutral Zn atom  and 3460 cm−1 (red). At n = 4, the most intense band is the red-shifted band centered at 3210 cm−1, along with weaker features centered at 3490 and 3710 cm−1. Similar to the zinc monomer–water complexes, [n = 4 present increased spectral broadening, which signifies several isomers contributing to the experimental spectrum. A broad, unresolved red-shifted band at 3230 cm−1, along with a shoulder at 3270 cm−1 is presented for n = 5. This red-shifted feature decreases in red-shift upon increasing cluster size, from 3240 cm−1 for n = 6−10, before red-shifting to 3220 cm−1 for n = 16 and 20. The shoulder feature at 3270 cm−1 for n = 5 also decreases in red-shift upon addition of water molecules from 3320 cm−1 in n = 6 to the broad, unresolved feature centered at 3470 cm−1 for n = 20.Very weak photodissociation of neutral Zn +  one Zn atom or (b) both Zn atoms, as shown in n = 2 as an example, IIa denotes the lowest-lying isomer with water molecules coordinated to one Zn atom, and 2IIa to both Zn atoms. Throughout the discussion, water binding motifs are also labelled. Water molecules which are directly bound to Zn are denoted core water molecules. Outer water molecules can bind to core water molecules via single, or double hydrogen bonds, denoted single acceptor (SA) and double acceptor (DA) motifs, respectively. Other binding motifs  the lowest-lying isomers have water molecules coordinated to one zinc atom. In this sense, one could expect that the water molecules will solvate one zinc atom in a similar fashion to the monatomic complexes, Zn+(H2O)n [n = 3 as an example, the addition of the Zn atom to Zn+(H2O)3 (forming Zn2+(H2O)3) changes the energetic ordering of isomers, shown in +(H2O)3, all three water molecules are directly bound to the central Zn atom, representing the lowest energy structure found. For Zn2+(H2O)3, this analogue . Interestingly, isomer IIIb, presenting one core and two outer water molecules, is the second lowest lying isomer (+6.3 kJ mol−1). In contrast, this analogue in Zn+(H2O)3 was calculated to lie 22.3 kJ mol−1 above the global minimum. These energetic differences between monatomic and dimer water complexes are observed in sizes n = 2–6, and are reflected in the observed IRMPD spectra. For the low-lying calculated isomers n = 4–6 in n+(H2O)n . Howevern = 1 (v2 configuration (Ia). The simulated spectrum of Ia presents two bands: one weak centered at 3568 cm−1, and one strong centered at 3670 cm−1, representing the symmetric and asymmetric stretches of water, respectively. These bands agree with the experimental band at 3580 cm−1, along with the weak shoulder at 3710 cm−1. However, the IRMPD band at 3580 cm−1 is strong and sharp, whereas the band at 3710 cm−1 is weak and broad. This is most likely an IRMPD effect, since two photons are typically required to dissociate Zn+(H2O), with a binding energy of 85 kJ mol−1. In this small system, intramolecular vibrational energy redistribution (IVR) is difficult. We may speculate that IVR works well for the symmetric band, so that both the first and second photon are absorbed in the vibrational ground state of the band, while IVR is accidentally hindered due to the sparse density of states for the asymmetric stretch. In this case, either the band position shifts due to anharmonicity from the fundamental to the hot band excitation, or the system cools by IR emission. Both effects can explain the experimental spectrum. For n = 1 a only onn = 2, two isomers are considered, IIa and IIb. Different to the case of the zinc monomer reported previously, [−1, the signature of the SA motif in isomer IIa. No such red-shifted bands were observed in the monomer analogue, Zn+(H2O)2 [n = 2 calculated at the CCSD/aug-cc-pVDZ//B3LYP/aug-cc-pVDZ level show that the 2-coordinate structure (IIb) is the lower-lying isomer by 6.5 kJ mol−1. Two more weaker bands are presented for isomer IIa at 3651 and 3726 cm−1, assigned to the localized core “free” O–H stretch and asymmetric outer O–H stretch, respectively. These bands are in reasonable agreement with the broad feature centered at 3680 cm−1. Isomer IIb presents one band at 3580 cm−1, along with two stronger bands at 3673 and 3695 cm−1, due to the symmetric O–H stretch and localized asymmetric O–H stretches of the two core water molecules, respectively. Similar to Zn+(H2O)2, the observed spectrum shows more intense symmetric O–H bands relative to the asymmetric O–H bands, along with increased broadening of the asymmetric bands. As described before, [−1, the IRMPD spectrum is composed of contributions from both isomers, IIa and IIb.In the case of viously,  for the n+(H2O)2 . It shou before,  we attrin = 3, along with the simulated spectra of the four lowest lying isomers, with water coordinated to one Zn atom, IIIa–IIId. The intense band at 3110 cm−1 is in good agreement with the simulated bands at 3105 cm−1  and 3129 cm−1  assigned to the SA motif. This observed band shows a shoulder at 3160 cm−1, presenting excellent agreement with the asymmetric O–H stretch in the core water in isomer IIIb at 3164 cm−1. Isomer IIIa presents an intense band at 3427 cm−1, a weaker band at 3387 cm−1 assigned as the in-phase, and out-of-phase core water molecules in the DA motif, respectively. These two bands are in good agreement with the broad experimental feature, displaying a maximum centered at 3445 cm−1. Spectral signatures of DA motifs were unobserved in Zn+(H2O)3. The strong band at 3680 cm−1 is in agreement with the simulated bands at 3680 cm−1 , 3686 cm−1 , 3646 cm−1 , 3701 cm−1 , and 3730 cm−1 . Given that isomer IIId is calculated to lie 11.7 kJ mol−1 above IIIa, it is more likely that isomers IIIa–IIIc are higher in abundance and contribute more to the overall IRMPD spectrum.n = 4, along with the simulated spectra of low-lying isomers IVa–IVd, are shown in n ≥ 4, it is more informative to discuss the spectra in terms of binding motifs, rather than individual isomers. Water binding motifs are outlined in the −1 is in good agreement with SA and an outer water bound to a double acceptor site (oDA) binding motifs in isomers IVa–IVc.The IRMPD spectrum for −1 matches the absorption of the DA binding motif in isomer IVa. The broad band at 3710 cm−1 presents satisfactory agreement with the simulated bands from isolated core, and outer waters in oDA, DA and S*A motifs present in isomers IVa–IVc. As observed, the simulated spectra in this wavelength region, between the symmetric and asymmetric stretches of isolated water (3657 and 3756 cm−1), become spectrally congested. Thus, this region is less diagnostic when assigning particular isomers and water binding motifs. Based on the red-shifted bands below 3650 cm−1, i.e., the spectral signatures of DA and SA motifs, the observed spectrum is composed of contributions from isomers IVa–IVc. The very broad feature centered at 3490 cmn = 5, along with the simulated spectra of low-lying isomers Va–Vd. Similar to the IRMPD spectrum of n = 4, the observed spectrum of n = 5 shows an intense red-shifted broad band centered at 3230 cm−1, along with an intense shoulder at 3270 cm−1. The intense feature is in good agreement with SA motifs in Va and Vb, and with the oDA motif in Vb. A DA/oDA combination band in Vb agrees with the shoulder at 3270 cm−1. The S*A motif in Vc is also in good agreement, however the red-shifted band at 3050 cm−1 (core oSA) presents less clear agreement. Another band at 3445 cm−1 (O–H stretch of outer water in oSA) in Vc shows some agreement, and could contribute to the overall broad region between the observed bands at 3230 and 3490 cm−1. The SA signature at 3278 cm−1 in isomer Vd is also in good agreement with the observed band at 3270 cm−1; however, the simulated band at 3183 cm−1 (core oSA) presents less agreement. Signatures of DA motifs in Va also fit with the observed bands at 3490 and 3540 cm−1. Outer single acceptor (oSA) motifs in Vc and Vd present agreement with the band at 3540 cm−1. All four isomers Va–Vd present bands within the observed features between 3230 and 3540 cm−1, assigned to SA, DA, oDA, and oSA binding motifs. The observed bands show an onset starting at ca. 3010 cm−1, which could be due to the most red-shifted band at 3050 cm−1 in isomer Vc (core O–H bound to the oSA motif). Isomer Vc is calculated to lie 7.4 kJ mol−1 above isomer Va, so will give a minor contribution to the observed spectrum, supporting the presence of the weak onset at ca. 3010 cm−1. Thus, the observed IRMPD spectrum mostly consists of isomers Va and Vb, with minor contributions from isomers Vc and Vd, along with other low-lying isomers we have not considered.n = 6, along with simulated spectra of low-lying isomers VIa–VId. The observed spectrum shows an intense band at 3320 cm−1, with a shoulder to the red at 3240 cm−1. Based on spectral assignments of Zn+(H2O)n, n = 2–6, [n = 2–5 in this study, this would imply a lower abundance of isomers with SA waters (most red-shifted), and a higher abundance of isomers with S*A waters (second most red-shifted). This assignment is supported when considering the strong out-of-phase S*A signature in VIa at 3283 cm−1. Another strong band at 3285 cm−1, the oDA signature, is also present in isomer VIa. DA signatures in VIa are in reasonable agreement with the observed broad feature between 3320 and 3445 cm−1. The most red-shifted band at 3193 cm−1 (core water bound to outer water in oSA) in VIb is in good agreement with the red-shifted shoulder at 3240 cm−1. Isomer VIb also presents bands at 3289 and 3317 cm−1  which are in good agreement with the observed intense feature at 3320 cm−1, and two more bands at 3458 cm−1 (core bound to outer water in D*A) and 3529 cm−1 (oSA) which present good agreement with the broad features between 3445 and 3540 cm−1. The observed shoulder at 3240 cm−1 is thus assigned to the core O–H bound to oSA in isomer VIb, in addition to the same binding motif in isomers we have not considered. Given that isomer VIb is still higher-lying, calculated as 7.8 kJ mol−1 above VIa, this isomer offers a minor contribution, reflected as an observed weaker shoulder band. Isomers VIc and VId are calculated to lie above VIa at 8.3 and 10.4 kJ mol−1, respectively, so are predicted to play a minor role.n = 2–6,  along win = 4–6, the bands in the region between 3657 and 3756 cm−1 are due to the asymmetric O–H stretches of different water binding motifs  giving a crowded and relatively less intense feature, thus this spectral range is less diagnostic when assigning the different binding motifs to the observed IRMPD spectrum.In each cluster size n = 2–6 along with the simulated spectra of isomers with water molecules coordinated to both Zn atoms. The structures of these isomers are presented in n = 2, 2IIa, presenting two bands at 3583 and 3687 cm−1, due to the symmetric and asymmetric O–H stretching bands, respectively. Both types of stretch are localized to one water, resulting in two pairs of bands, with each pair coalescing forming a band . These simulated bands are in good agreement with the experimental bands at 3590 and 3680 cm−1. Similar to the spectrum of IIb, the asymmetric bands are more intense than the symmetric, with the opposite shown in the experimental spectrum. The experimental IRMPD spectrum of n = 2 was assigned to contributions from isomers IIa and IIb. However, given that the spectrum for 2IIa is in good agreement with the observed spectrum, and is calculated to lie only 4.4 kJ mol−1 above IIa, we cannot rule out contributions from 2IIa. n = 3, along with simulated spectra from isomers 2IIIa–2IIId. Simulated bands at 3095 cm−1  and 3083 cm−1  agree well with the experimental band at 3110 cm−1, assigned as core O–H stretches in SA motifs. However, none of these simulated spectra can reproduce the observed feature at 3160 cm−1. Isomers 2IIIa and 2IIIb however, are in good agreement with the SA signature at 3110 cm−1, and are calculated to lie 9.9 and 10.4 kJ mol−1 above IIIa, respectively. Thus, isomers 2IIIa and 2IIIb could offer a minor contribution to the IRMPD spectrum, with major contributions from isomers IIIa–IIIc.2IVa–2IVd, is shown for n = 4 in 2IVa presents a red-shifted band at 3147 cm−1, assigned as the two equivalent SA motifs, and agrees well with the observed band at 3210 cm−1. Simulated bands at 3206 and 3252 cm−1 in 2IVc, the in-phase and out-of-phase core DA O–H stretches, respectively, present good agreement with the broad feature at 3210 cm−1. The simulated band at 3184 cm−1 in isomer 2IVd, the SA motif, is also in agreement with this observed band. Evidence of the DA signature is also presented in the simulated spectrum for 2IVb at 3452 cm−1. Though these simulated bands present agreement with the observed spectrum, isomers 2IVa–2IVd lie ≥ 9.7 kJ mol−1 above IVa, so are expected to have a minor contribution to the IRMPD spectrum. The IRMPD spectrum, along with the simulated spectra of n = 5, along with the simulated spectra of 2Va–2Vd, is presented in −1 in IVa and 2IVa to 13.1 kJ mol−1 in Va and 2Va). Thus, given the large energy differences between isomers Va–Vd and 2Va–2Vd, the observed IRMPD spectrum largely consists of singly coordinated zinc isomers, namely Va and Vb, with minor contributions from other singly coordinated, as well as doubly coordinated, isomers.Upon addition of another water molecule, the IRMPD spectrum for n = 6, along with the simulated spectra of 2VIa–2VId, is presented in n = 5, the doubly coordinated isomers 3 , Zn dissociation is calculated as 141 kJ mol−1 (1.46 eV), lower than the previous calculations from Gutsev [2, the latter determined by gas-phase charge transfer bracketing experiments [2+, assuming solely ion-induced dipole bonding interactions, giving an internuclear distance of 3.00 Å, which is much higher than the Zn–Zn distance calculated by Gutsev [2+ is most likely due to covalent bonding, primarily with 4sσ bonding character. This would imply minor contributions from 3d orbitals, yielding a bond order of 0.5 and an equal charge distribution on both Zn atoms. Similar bonding mechanisms have been proposed in collision-induced dissociation measurements of Mn2+, [2–, [2+. For almost all cluster sizes the binding energy of zinc is higher than the binding energy of a water molecule, and for both Zn dissociation and water dissociation, the binding energy (BE) decreases with increasing cluster size. Blue bars in 2O)), which for cluster sizes n = 1 and 4–6 present a positive energy difference. Given these positive binding energy differences, we expect water dissociation dominates, which is concordant with our IRMPD spectra of n = 1 and 4–6. For cluster sizes n = 2 and 3, the binding energy of neutral Zn is lower than that of water, presenting negative energy differences  in n = 2 and 3. Given that we observe only water dissociation in the IRMPD spectrum of Zn2+(H2O)2, we believe that the binding energy difference is not sufficiently large in order for the Zn dissociation channel to be observed experimentally. The small binding energy difference of −2.1 kJ mol−1 in n = 2 is also within error of our calculations. For n = 3, however, the dominant channel is water dissociation, with Zn dissociation presenting a weaker, but prominent, spectrum. We attribute the appearance of the Zn channel to the binding energy difference of −6.0 kJ mol−1, which, although a weaker channel, is enough to be observed in the IRMPD spectrum. In larger clusters, n > 3, further factors suppressing the Zn dissociation channel could be attributed to the decrease in water binding energies, resulting in the dissociation of weakly bound outer shell water molecules, preferred over Zn dissociation.In addition to dissociation of water molecules, we also observe the loss of a neutral zinc atom for Zn2+(H2O)3 . This chm Gutsev  n clusters [ns1 valence electron configuration, which caused incoming ligands to experience repulsion from the occupied s orbital. Thus, water molecules bind to the same side of the metal center, even at larger cluster sizes. A similar effect is observed in Zn2+(H2O)n clusters, whereby incoming water molecules bind to one Zn atom and avoid binding to the second Zn atom.or n = 8 a presentn = 10 is presented in −1, with a maximum at 3460 cm−1, along with a shoulder to the red at 3280 cm−1, and a blue shoulder at 3530 cm−1. A sharper band to the blue at 3700 cm−1 is also shown. The low-lying isomers of Zn2+(H2O)10 are presented in −1) when compared to the smaller clusters. The simulated spectra of all four isomers present many bands, which accounts for the broad absorption in the observed spectrum. The spectrum of Xa, however, presents a red-shifted band at 2885 cm−1, assigned to the O–H stretch of an outer water hydrogen-bonded to three other outer water molecules, which is not observed experimentally. This red-shifted band was also calculated in the simulated spectrum of the putative global minimum structure for Zn+(H2O)10, and signifies significant weakening of the O–H bond and emergence of the mobile proton. Just as is the case in this study, this red-shifted band was not observed in monatomic zinc-water clusters. Isomers Xb–Xd do not present such red-shifted bands, and instead show more outer water molecules in SA binding motifs. This would suggest that warmer isomers  are present in the ICR cell. This is concordant with our previous study on Zn+(H2O)n clusters, whereby entropic effects (higher presence of less rigidly bound SA motifs) dominate enthalpic effects at higher temperatures [The IRMPD spectrum of n = 16 and 20 n [The IRMPD spectra of larger clusters 6 and 20  look quan+(H2O)n , there a−1 was observed previously in the D2 “tagged” vibrational predissociation spectra of M2+OH–(H2O)n=1–5  by Johnson and co-workers [+(H2O)n [2+(H2O)16,20; thus, we rule out formation of the Zn–HZnOH+ motif in larger clusters. The infrared signature of the mobile proton; a weak, broad, structureless absorption between 2800 and 3500 cm-workers . This si[+(H2O)n , is also64Zn 99.4%, STB Isotope Germany, GmbH), producing a plasma. This plasma is then entrained into a pulse of the desired gas mixture (H2O in helium) produced via a homebuilt piezoelectric valve. The ensuing pulse is cooled via supersonic jet expansion into the source chamber. The gas pulse traverses through a skimmer (forming the molecular beam), and ions are guided via an electrostatic lens setup into the center of the ICR cell. Ions of the composition Zn2+(H2O)n (n = 1–20) are then stored and mass-selected within the 4.7 T magnetic field [−10 mbar). The ICR cell is surrounded by a copper jacket, whereby the temperature of the cell is controlled and cooled to ca. 80 K via liquid nitrogen [All experimental measurements were performed on a modified 4.7 Tesla Bruker/Spectrospin CMS47X FT-ICR mass spectrometer ,82,83,84ic field  under ulnitrogen ,90 for anitrogen ,94,95,962 window [−1 region, probing the O–H symmetric and asymmetric stretching modes. Specific details on the laser setup can be found in previous publications [σ, are calculated by using a modified Beer–Lambert equation:I0 represents the intensity of the precursor ion, iI the fragment ion intensity, λ the laser wavelength, P the laser power, t the irradiation time, h the Planck constant, A the area of the laser beam and k an empirical factor which corrects for any contributions due to BIRD. On the opposite side of the magnet, the output radiation of a tunable IR OPO laser system  is aligned into the cell through a CaF2 window . Absorpt2 window . Monitorications ,99. To a2+(H2O)n were calculated using density functional theory (DFT). Calculations were performed by using the B3LYP functional coupled with the aug-cc-pVDZ basis set. Simulated infrared spectra were generated by implementing Gaussian functions to the band positions, each with a full width at half maximum (FWHM) of 20 cm−1, using a scaling factor of 0.96. All structures considered represent local minima and are in the doublet spin multiplicity corresponding to the ground state. Other multiplicities, such as quartet or sextet, lie considerably higher in energy . Binding energies for the low-lying structures for n = 0–6 were calculated through single-point recalculation of B3LYP/aug-cc-pVDZ at the coupled cluster singles and doubles (CCSD) level with the aug-cc-pVDZ basis set. Charges on atoms were calculated by using the CHELPG scheme, [To complement the experimental findings, the structures, along with their corresponding infrared spectra, of Zn scheme,  with the scheme, . 2+(H2O)n, n = 1–20) were formed in the gas-phase by laser vaporization, size-selected, and stored in the center of an ICR cell cooled to ca. 80 K. Infrared multiple photon dissociation spectra were recorded for each cluster size revealing structural information and the nature of water binding sites to Zn2+. Photodissociation of intact water molecules is the dominant channel for every cluster size, with the exception of n = 3, whereby Zn photodissociation is also observed as a weaker channel. Cationic zinc dimer–water complexes  region may help to further support these claims of asymmetric solvation.n = 3 is rationalized by an interplay of water and Zn binding energy. Calculated binding energies show subtle differences in water binding energy vs. Zn binding energy for smaller clusters, with a significant decrease in Zn binding at n = 3. This anomalous Zn binding energy at n = 3 helps to rationalize the observed Zn dissociation in the infrared spectrum.Zn photodissociation observed in


Vegetarianism is on the rise worldwide and its importance is being emphasized in various ways, such as in its sustainability, environmental, food system, and ethical aspects. The purpose of the study is to identify motivations behind food choices and dietarian identity, to investigate the perceptions about plant-based foods, and to identify differences between vegetarians and omnivores. We conducted an online survey of 245 vegetarians and 246 omnivores. There was a significant difference between vegetarians and omnivores. In food choice motivations, vegetarians scored higher in the factors of ‘ethical concern’, ‘health’, and ‘convenience and price’, while omnivores responded higher in ‘sensory appeal’ and ‘weight control’ factors. In the dietarian identity, vegetarians scored higher in the ‘complex motivation’ and ‘strictness’ factors, while on the other hand omnivores scored higher in ‘out-group regard’ and ‘public regard’ factors. Although the reasons can be different, we confirmed that both vegetarians and omnivores are positive toward plant-based foods. Our results suggest that different strategies will be needed to promote plant-based food consumption to vegetarians and to omnivores. There is widespread consensus around the world that animal-product consumption needs to be reduced to avoid climate change, as livestock production accounts for a significant portion of greenhouse gas (GHG) emissions ,2,3,4. TA study  claimed As the benefits of vegetarianism have become more widely known, the number of vegetarians has steadily increased worldwide , but totVarious studies have been conducted on the motivations behind vegetarianism. One study  conducteSeveral studies have investigated the differences between vegetarians and omnivores. A qualitative study  found thDietarian identity is a comprehensive structure that reflects all aspects of self-awareness regarding a person’s choice of foods . It is fFood choice motivation refers to the reason or motivation of a consumer to choose a given food . VariousVarious terms are used to refer to vegetarians, such as vegetarian, vegan, pescatarian, and pollotarian. Vegetarians are generally defined as individuals who do not consume meat, poultry, and fish ,38. VegaThe objective of the study is to investigate and differentiate the dietary identities, food choice motivations, and personal expectations toward plant-based foods between vegetarians and omnivores. For this, the following hypotheses were made:Hypothesis 1 .Food choice motivation may differ between vegetarians and omnivores.Hypothesis 2 .Dietarian identity may differ between vegetarians and omnivores.Hypothesis 3 .Dietary type may determine perception and behaviors toward plant-based food products.This study was conducted on a total of 491 individuals, comprising 245 vegetarians (vegan or vegetarian or semi-vegetarian) and 246 omnivores in the Republic of Korea. The criteria for the vegetarian participants were as follows: (i) individuals who perceive themselves as vegetarians ; https://d8aspring.post-survey.com/open/?key=Og0UQzwF, last accessed on 20 May 2020); the completed questionnaires with the participant’s consent for participation were recorded.To select the participants, non-probability sampling was used. To recruit individuals satisfying the criteria, a notice and the link to the questionnaire were posted on two online sites: Hanulvut Vegetarians , which has the largest number of members among the online communities, and the Korean Vegetarian Association. In addition, through acquaintances, the notice and the link to the questionnaire were shared with vegetarianism communities, such as the Vegetarianism Peace Alliance, and various social network sites (KAKAOTALK group chat rooms). The participants were those who read and understood the notice and participated in the questionnaire via the link .The questionnaires for vegetarians were completed first; then, in the same proportions according to the age and sex of the vegetarian participants, the questionnaires for omnivores were completed. The online surveys of the omnivores and the vegetarians were carried out through DataSpring, Inc.  . The survey was conducted from May 14, 2020 to May 26, 2020. The survey proceeded if the participants, who had read the study’s purpose and methods, subsequently agreed to participate.The questionnaires comprised 95 questions in total, including those for dietary type, perception toward plant-based foods, vegetarian experience, and demographic factors. To compare vegetarians and omnivores, the survey in this study contained two questionnaires. The questions regarding dietarian identity and food choice motivation were on a seven-point scale, whereas all the other questions were on a nominal scale. We used randomization when technically implementing FCQ and DIQ questionnaires on the web as a strategy to reduce the effectiveness of question-order bias, one of response bias. Therefore, the overall questionnaire order is the same for all respondents with FCQ, DIQ, perception of plant-based food products, dietary type, vegetarian experience, and demographic information; the order of questions in the FCQ and DIQ questionnaires was different for each respondent. The design of the entire questionnaire is presented in Although scholars have different descriptions of the specific types of vegetarianism, this study uses the categories presented by studies ,51 to deFor dietary types, responses were made on nominal scales to the following two questions: eight categories  and four labels  according to the categories and definitions provided in In addition, participants responded to DIQ’s dietary pattern question, the answers of which were presented in The Food Choice Questionnaire (FCQ) with 44 questions of nine factors was used to assess food choice motivation. The FCQ comprised 36 questions of the original tool developed by a study  and eighThe Dietarian Identity Questionnaire (DIQ) with 33 questions of eight factors, developed by the study , was useAccording to the , before “I generally do not eat red meat.”“I generally do not eat poultry.”“I generally do not eat fish.”“I generally do not eat dairy.”“I generally do not eat egg.”“I generally eat all of these food groups.”The term ‘dietary pattern’, which appears repeatedly in the DIQ questions, refers to the dietary type of each person who answered this question.The questionnaires were modified in accordance with the study purpose, with consideration of previous studies for investigating perception and behaviors regarding plant-based food products. The operational definition of “plant-based food products” as used in the questionnaires covered a broad range of plant-based foods but excluded completely natural or whole-plant-based foods. Hence, vegetables, fruits, whole grains, and beans without any processing or cooking were excluded. The definition of plant-based food products thus included traditional soybean-based processed foods , plant-based dairy substitutes, plant-based meats, plant-based bakery products, and plant-based snacks, and this study focused on these plant-based food products. The questions addressed general perception, purchase intention, and preferred labels.Only the vegetarian respondents were asked to respond to the following four questions related to the vegetarian experience: motivation, reason for continuation (single/multiple choice), duration of vegetarian diet.Because the motivation might change when vegetarianism is maintained for a long time ,37,44, tEight questions  were used for the demographic information survey.SPSS Statistics 22.0 software was used to analyze the 491 questionnaires (245 from vegetarians and 246 from omnivores) collected through the online surveys. To identify the demographic characteristics of the participants and determine their perceptions of plant-based food products, frequency analysis was performed. For the 44 questions on the FCQ about food choice motivation and the 33 questions on the DIQ about the dietarian identity of vegetarians and omnivores, exploratory factor analysis (EFA) was performed to test the factor structure and question validity, and to evaluate the reliability. To determine the differences according to the vegetarianism or omnivorism dietary types, an independent t-test was performed.Among the 245 vegetarian participants, the self-identified vegetarianism dietary types were as follows: 124 vegans (50.6%), 9 ovo-vegetarians (3.7%), 15 lacto-vegetarians (6.1%), 24 lacto-ovo-vegetarians (9.8%), 37 pescatarians (15.1%), 13 pollotarians (5.3%), and 23 flexitarians (9.4%). When the types were identified based on the broader categories, 110 participants perceived themselves as vegans (44.9%), 53 as vegetarians (21.6%), and 82 as semi-vegetarians (33.5%). The self-identified types were different from those categorized on the basis of the participants’ responses and detailed criteria: 124 vegans (50.6%), 48 vegetarians (19.6%), and 73 semi-vegetarians (29.8%).The motivations were as follows: health for 89 participants (36.3%), animal protection, 85 (34.7%), environmental protection, 37 (15.1%), religion, 15 (6.1%), influence of family or friend, 6 (2.4%), and other, 13 (5.3%).The reason for continuation with the largest number of participants was animal protection at 95 (38.8%), followed by health, 82 (33.5%), environmental protection, 39 (15.9%), religion, 13 (5.3%), influence of family or friend, 5 (2.0%), and other, 11 (4.5%).In the multiple choice for reasons for continuation, the results showed that animal protection was among the reasons for 177 participants (72.2%), environmental protection for 173 (70.6%), health, 164 (66.9%), influence of family or friend, 25 (10.2%), religion, 22 (9.0%), and other, 14 (5.7%). Three reasons were most frequently given by 94 participants (38.4%), followed by one reason by 72 (29.4%), two reasons by 48 (19.6%), four reasons by 30 (12.2%), and five reasons by 1 (0.4%).The maintenance durations were as follows: ≥20 years for 22 participants (9.0%), ≥10 years and <20 years for 40 (16.3%), ≥5 years and <10 years for 17 (6.9%), ≥4 years and <5 years for 14 (5.7%), ≥3 years and <4 years for 20 (8.2%), ≥2 years and <3 years for 26 (10.6%), ≥1 year and <2 years for 47 (19.2%), ≥6 months and <1 year for 44 (18.0%), and <6 months for 15 (6.1%).Factor 1 was labeled Ethical Concern because the responses were “Has been produced in a way that animals’ rights have been respected”, “Has been produced in a way that animals have not experienced pain”, “Has been prepared in an environmentally friendly way”, “Comes from a country in which human rights are not violated”, “Has been produced in a way which has not shaken the balance of nature”, “Is packaged in an environmentally friendly way”, and “Has been prepared in a way that does not conflict with my political values”. The eigenvalue of Factor 1 was 5.142 and the explanatory power was 15.123%.Factor 2 was labeled Health because the responses were “Keeps me healthy”, “Contains no additives”, “Contains no artificial ingredients”, “Contains a lot of vitamins and minerals”, “Is good for my skin/teeth/hair/nails, etc.”, “Contains natural ingredients”, “Is nutritious”, and “Is high in fiber and roughage”. The eigenvalue of Factor 2 was 4.901 and the explanatory power was 14.416%.Factor 3 was labeled Convenience and Price because the responses were “Is easy to prepare”, “Can be cooked very simply”, “Takes no time to prepare”, “Is easily available in shops and supermarkets”, “Is not expensive”, “Can be bought in shops close to where I live or work”, and “Is cheap”. The eigenvalue of Factor 3 was 3.840 and the explanatory power was 11.293%.Factor 4 was labeled Mood because the responses were “Keeps me awake/alert”, “Helps me to cope with life”, “Cheers me up”, “Makes me feel good”, and “Helps me cope with stress”. The eigenvalue of Factor 4 was 3.267 and the explanatory power was 9.608%.Factor 5 was labeled Sensory Appeal because the responses were “Smells nice”, “Has a pleasant texture”, “Looks nice”, and “Tastes good”. The eigenvalue of Factor 5 was 2.725 and the explanatory power was 8.014%.Factor 6 was labeled Weight Control because the responses were “Is low in calories”, “Helps me control my weight”, and “Is low in fat”. The eigenvalue of Factor 6 was 2.405 and the explanatory power was 7.075%.Factor 1 was labeled Complex Motivation because it was shown to comprise the five factors of centrality, personal motivation, prosocial motivation, private regard, and moral motivation in the original DIQ. The questions in detail were, “Following my dietary pattern is an important part of who I am”, “My dietary pattern has a big impact on how I think of myself”, “My dietary pattern defines a significant aspect of who I am”, “I follow my dietary pattern because eating this way improves my life”, and so on. The eigenvalue of Factor 1 was 9.675 and the explanatory power was 31.21%.Factor 2 was labeled Out-group Motivation because it was shown to comprise the factors of out-group motivation in the original DIQ. The questions in detail were, “I judge people negatively for eating foods that go against my dietary pattern”, “Seeing people eat foods that go against my dietary pattern makes me upset or angry”, “I view people as less moral for eating foods that go against my dietary pattern”, “If I see someone eat foods that go against my dietary pattern, I like him or her less”, and so on. The eigenvalue of Factor 2 was 6.500 and the explanatory power was 20.967%.Factor 3 was labeled Public Regard because it was shown to comprise the factors of public regard in the original DIQ. The questions in detail were, “People who follow my dietary pattern tend to receive criticism for their food choices”, “People who follow my dietary pattern are judged negatively for their food choices”, and “Following my dietary pattern is associated with negative stereotypes”. The eigenvalue of Factor 3 was 3.322 and the explanatory power was 10.715%.Factor 4 was labeled Strictness because it was shown to comprise the factors of strictness in the original DIQ. The questions in detail were, “I can be flexible and sometimes eat foods that go against my dietary pattern”, “From time to time, I eat foods that go against my dietary pattern”, and “I would eat a food product that goes against my dietary pattern if I were to hear that it tastes exceptionally good”. The eigenvalue of Factor 4 was 2.521 and the explanatory power was 8.133%.To test H1, the first hypothesis of this study, t-tests were performed for the means of the FCQ factors based on dietary type, and the results are shown in p < 0.001), that for Health was significantly higher for vegetarians (5.64 ± 0.97) than for omnivores (5.13 ± 0.98) (p < 0.001), and that for Convenience and Price was significantly higher for vegetarians (5.91 ± 1.04) than for omnivores (5.39 ± 0.83) (p < 0.001). For Sensory Appeal, the score was significantly lower for vegetarians (4.73 ± 1.19) than for omnivores (5.39 ± 0.75) (p < 0.001). Likewise, for Weight Control, the score was significantly lower for vegetarians (4.46 ± 1.46) than for omnivores (4.81 ± 1.26) (p < 0.01). For Mood, no significant difference was found between vegetarians (5.56 ± 1.00) and omnivores (5.57 ± 0.82) (p = 0.951).Among the factors of food choice motivation, the score for Ethical Concern was significantly higher for vegetarians (5.98 ± 0.78) than for omnivores (4.39 ± 1.08) , and the score for Strictness was also significantly higher for vegetarians (4.99 ± 1.59) than for omnivores (3.34 ± 1.04) (p < 0.001). For Out-group Motivation, the score was significantly lower for vegetarians (4.61 ± 1.50) than for omnivores (5.65 ± 1.30) (p < 0.001). For Public Regard, the score was also significantly lower for vegetarians (3.77 ± 1.40) than omnivores (5.54 ± 1.35) (p < 0.001).Among the factors of dietarian identity, the score for Complex Motivation was significantly higher for vegetarians (5.59 ± 1.00) than for omnivores (3.27 ± 1.17) (p < 0.001). For vegetarians, the most frequent response was Very high , followed by High . For omnivores, in contrast, the most frequent response was Slightly , followed by Moderately . The results of the crossover analysis for the preferred labels of plant-based foods based on dietary type showed χ2 = 221.098, indicating a significant difference at the level of 0.001. Most vegetarians were found to prefer the label, “Vegan foods” , whereas most omnivores preferred the label, “Plant-based foods” .The result of the crossover analysis of the perception toward plant-based food products based on dietary type showed χ2 = 64.739, with a significance probability of 0.000, indicating a significant difference in the perceptions toward plant-based food products between vegetarians and omnivores . The numTo compare food choice motivation and dietarian identity between vegetarians and omnivores, and to investigate the differences in the perception of plant-based foods, an online survey was conducted on a total of 491 participants. Based on the results of the statistical analyses, all three hypotheses could be accepted.Among the factors for food choice motivation, the scores for Ethical Concern, Health, and Convenience and Price were higher for vegetarians, whereas the scores of Sensory Appeal and Weight Control were higher for omnivores. The food choice motivation of vegetarians differed in specific ways from that of omnivores, and the results agreed with those of previous studies ,55 to coAmong the factors for dietarian identity, the scores for Complex Motivation and Strictness were higher for vegetarians, whereas the scores of Out-group Motivation and Public Regard were higher for omnivores; these results coincided with those of one study . For vegRegarding the perceptions of plant-based food products, 148 vegetarians (60.4%) and 160 omnivores (65.0%) replied that they were “Positive”, indicating a higher proportion of individuals with a positive attitude. The result is in line with the results of a previous study , which rWith regard to the purchase intentions for new plant-based foods, a significant difference was found between vegetarians and omnivores. For vegetarians, the most frequent responses were Very High and High, whereas Slightly and Moderately were frequent for omnivores. Although the purchase intentions for new plant-based foods were higher in vegetarians, the intentions were not entirely negative in omnivores.In considering the preferred labels for plant-based foods, most vegetarians were found to prefer the “Vegan foods” label and most omnivores were found to prefer the “Plant-based foods” label. We therefore consider that labeling with “Plant-based foods” would contribute to increasing the general consumption of these foods.Despite the significant results, there are several limitations with this study. First, the traditional dietary habits in South Korea, mostly based on vegetables, are different from those in the West, but over time they became Westernized and meat consumption increased. Thus, a survey of the differences between generations is required but was not performed in this study, and future studies should investigate the differences between generations for comparative analysis. Second, because vegetarianism is one term that refers to people who eschew all animal-based foods, as well as those who selectively allow certain animal products, differences may be found in food choice motivations and dietarian identities among vegetarians. In this study, the type of vegetarianism was not specified in comparing vegetarians with omnivores, and further studies should separately analyze the specific vegetarian types for more accurate comparison.This study is significant in having comparatively analyzed the food choice motivations and dietarian identities, as well as the perceptions of plant-based foods based on dietary type in Korean consumers, where the interest in vegetarianism and the number of vegetarians have increased.All three hypotheses were accepted. In H1, concerning the food choice motivations, vegetarians scored higher in the factors of ‘ethical concern’, ‘health’, and ‘convenience and price’, while omnivores responded higher in the ‘sensory appeal’ and ‘weight control’ factors. In the case of H2, concerning dietarian identity, vegetarians scored higher in the ‘complex motivation’ and ‘strictness’ factors, on the other hand omnivores scored higher in ‘out-group regard’ and ‘public regard’ factors. Regarding H3, concerning the perceptions of plant-based foods, vegetarians and omnivores both had the highest percentage of ‘positive’ responses first, but there was a difference in that the second most common answers were ‘ambivalent’ for vegetarians and ‘no opinion’ for omnivores.Based on the findings of this study, further studies should continue to investigate vegetarianism in South Korea with a multidisciplinary approach to contribute to the development of more sustainable dietary habits and cultures. In addition, through such studies, Korean society is anticipated to become healthier as more varied choices are allowed. What vegetarians value, in reality, is not just the aspects of dietary habits, but rather the overall lifestyle, such as minimizing their use of disposable products in daily life and promoting the use of products without animal testing. In the future, therefore, extensive research should be conducted to investigate the diverse aspects of vegetarianism in addition to dietary habits. Furthermore, cross-cultural studies of vegetarianism in various countries should be conducted.


B2M and PTEN are considered potential therapeutic targets that can improve the immune response. Patients with a high immune subtype can generally obtain a better immune prognosis effect, and the prognosis may be improved when combined with TGF-β inhibitors.Tumour immunotherapy combined with molecular typing is a new therapy to help select patients. However, molecular typing algorithms related to tumour immune function have not been thoroughly explored. We herein proposed a single sample immune signature network (SING) method to identify new immune function-related subtypes of cutaneous melanoma of the skin. A sample-specific network and tumour microenvironment were constructed based on the immune annotation of cutaneous melanoma samples. Then, the differences and heterogeneity of immune function among different subtypes were analysed and verified. A total of 327 cases of cutaneous melanoma were divided into normal and immune classes; the immune class had more immune enrichment characteristics. After further subdividing the 327 cases into three immune-related subtypes, the degree of immune enrichment in the “high immune subtype” was greater than that in other subtypes. Similar results were validated in both tumour samples and cell lines. Sample-specific networks and the tumour microenvironment based on immune annotation contribute to the mining of cutaneous melanoma immune function-related subtypes. Mutations in  Cancer is not a single disease but a collection of multiple biological entities, and each has its own molecular characteristics and clinical significance . TraditiCurrently, intergenic relationships can be obtained in three ways: (1) gene regulation networks based on existing public database information; (2) gene regulation network based on intergenic correlation  or causaAs a representative immunotherapy, cutaneous melanoma (SKCM) has a high mortality rate given its high malignancy, high incidence, and easy metastasis . At presHere, we comprehensively analysed the molecular profiles of SKCM, including omics characteristics, immune mechanisms, and stromal cell infiltration abundance based on sample-specific networks, to identify subtypes related to immune function in SKCM and the molecular characteristics behind their subtypes.n = 82], GSE23376 [n = 22], GSE19234 [n = 44], GSE15605 [n = 58]), and 206 tumour samples (n = 49) in cutaneous melanoma were downloaded from DepMap .The discovery cohort used in this study was from The Cancer Genome Atlas (TCGA) under the SKCM archive with a total of 327 tumour samples; gene expression, mutation, DNA methylation, and clinical data were retrieved. An external validation cohort including 214 SKCM data and paracancerous tissues was obtained from the GEO database (GSE7553  [n = 82]GSE19234  [n = 44]GSE15605  [n = 58] samples  were merWe selected the C7 data set in the MSigDB database as the annotated database and the modified PAN method as SING (single sample immune signature network), which followed the analytic process below .Feature selection(1)The high-dimensional nature of gene expression data makes it necessary to reduce dimensionality before analysis. For each gene data set, the top 500 genes were selected according to the order of their total variance and included in subsequent analysis and calculation.(2)Construction of gene and immune annotation correlation matrix(3)(4)Development of sample-specific network(5)The symmetric correlation matrix (6)Computing network topology information.Once the discrete network construction of each sample was completed, the topological property “degree” of the network was calculated and obtained for subsequent clustering analysis. For a given sample Clustering is an effective algorithm for molecular typing and has been successfully applied in the molecular typing of many kinds of cancer ,27. We uAs the degree of infiltration is related to the prognosis of immunotherapy in immune and stromal cells, we used the R package “MCPcounter” (v1.2.0)  to calcuCell dissolution activity, also known as cell killing activity, can be used to characterize the immunogenic nature  of tumoup values were adjusted by the false discovery rate (FDR). Genes with fold change ≥ 2 and FDR < 0.05 were considered differentially upregulated genes, while those with fold change ≤ 1/2 and FDR < 0.05 were considered differentially downregulated genes.The standard analysis process of “DESeq” (v1.30.1)  was usedThe gene enrichment analysis included GO functional annotation and KEGG pathway analysis. The GO functional annotation was completed by the DAVID 6.8 ,34 onlinBased on cancer somatic mutation data, we used the R package “MutSigCV” (v2.0)  to identp value < 0.01, the probe showed a hypermethylation level; when log2FoldChange < 0 and the adjusted p value < 0.01, the probe showed a low methylation level (R package “ChAMP” v2.20.1) [We analysed two methylation statuses of the promoter: (1) hypermethylation status and (2) demethylation status. First, low-quality probes were filtered and differentiated CpG sites were identified. This result suggested that when log2FoldChange > 0 and the adjusted v2.20.1) .p < 0.05). Univariate Cox proportional hazards regression was used to calculate the predictors associated with cancer survival [To confirm whether there was a significant difference in survival between subtypes, a Kaplan–Meier curve  was usedsurvival . After isurvival  was usedsurvival ,44 was uBased on the degree topological property matrix of immune annotation sample-specific as input matrix, the optimal number of clusters were tested from one to six. The sample data were divided into two categories A. Then, p = 0.008). Then, univariate Cox regression was used to analyse those factors that may affect the survival of SKCM patients (p < 0.05). The nomogram  was also observed: the “new-normal class” was the worst, followed by “immune1 class”, and “immune2 class” was the best , and the abundance of MDSCs was the highest in the “immune inactivation subtypes” and lowest in the “high immune subtype” (p = 9.1 × 10−15).Based on 1117 differentially expressed genes between the “high immune subtype” and “low immune subtype”, GO functional annotation and KEGG pathway enrichment were further analysed. These differentially expressed genes were mainly related to the immune response, inflammatory response, T cell proliferation, leukocyte proliferation, and chemokine-mediated signalling pathways B. Using p-value < 0.01, including NRAS, BRAF, B2M, PTEN, TP53, and CDKN2A , and mutation of this pathway is an important factor that causes growth and development of melanoma. These results indicate that NRAS and BRAF mutations were specific characteristics of the two subtypes. Additionally, B2M and PTEN mutations occurred only in the “immune inactivation subtype”.The influence and interaction between various factors in the tumour were complex, and the methylation status and gene mutations in the tumour had a strong relationship with gene expression, which would affect tumour occurrence and development. Therefore, we continued to explore the differences between the “high immune subtype” and “low immune subtype” based on tumour methylation and gene mutation. In this study, 21,981 probes were screened for methylation differences between high and low immune subtypes; 982 probes were hypermethylated, and 4620 probes were demethylated. After mapping these probes to genes and annotating with immune gene sets, a total of 597 genes showed hypermethylation but were epigenetically silenced in the “high immune subtype”, among which 10 genes were immune system related. In addition, 1490 genes were demethylated, of which 60 were related to immunity. Then, six significantly mutated genes were identified with a d CDKN2A . NRAS app = 0.00058; p = 0.03; p = 3.2 × 10−9; There were no significant differences in TMB levels between the “high immune subtype” and “low immune subtype”. Because the TMB level of the “immune class” was significantly higher than that of the “normal class” (p < 0.05).In this study, four independent cohorts were integrated as a verification set for supervised analysis (206 tumour samples). First, the existence of an immune class (Cluster 1) and a normal class (Cluster 2) were verified, with the immune class having higher immune signatures . To furtn = 49), the optimal clustering number was three according to the BIC value (p < 0.05), we found significant differences among them. Tumour immune infiltration in the “C1” was significantly higher than that in the other two clusters, which was highly similar to the “high immune subtype”. However, cytolytic activity score among three clusters were not significant as the expressions of the cell lines were too low . Specifically, more tumour grade samples were III or IV in the “high immune subtype” , and the proportion of metastatic samples was higher .For 327 samples, the heterogeneity in clinical features among the three immune subtypes was explored from the following six perspectives : (1) agePSME, CDC42, CMTM6, HLA-DQB1, HLA-C, CXCR6, CD8B, TNFSF13) and the five-immune-associated gene (IAG) signature , both published signatures [p < 0.001, HR = 1.765, 95% CI: 1.297–2.402; p = 0.0667, HR = 1.328, 95% CI: 0.9807–1.797). Additionally, we found significant differences in the risk score between the three immune subtypes (p < 0.05). Among them  signature  is an important adjunct to major histocompatibility complex class 1, and its absence leads to a decline in MHC-1 expression, affecting antigen presentation and resulting in PD-1 drug resistance [PTEN, as a tumour suppressor gene [BRAF, and MEK inhibitor in stage III-IV melanoma as significantly improving PFS of patients. Based on the risk score between the three immune subtypes, “high immune subtype” showed better prognostic value. Therefore, we speculated that patients with “high immune subtype” biological characteristics can generally obtain a better immune prognosis and that the immune prognosis is improved if combined with TGF-β inhibitors. In the “low immune subtype”, only one significantly mutated gene, NRAS, was found, which was considered a molecular feature of this subtype.We herein started by considering the tumour microenvironment and tumour cells and built the SING method by immune annotation information as background to explore the immune function of cutaneous melanoma-related subtypes of skin. The SING algorithm is helpful to identify immune functions related to subtypes. The “immune inactivation subtype” had two unique genetic mutations, ne cycle . B2M gensistance . A meta-sistance  showed tsistance . PTEN, asor gene , was fousor gene ,55. TGF-sor gene ,56,57 tosor gene ,59. In 2sor gene  suggestesor gene  proposedAlthough we divided the immune subtypes of cutaneous melanoma from the effects of tumour cells and the tumour microenvironment, there were still some inextricable links among various factors that we did not consider. We also have not considered the interaction between factors from comprehensive perspectives. Not with-standing its limitation, this study does suggest that the research of cancer typing based on immune function can be enhanced by using a sample-specific network. Further study is needed on how to combine the key factors that influence the response to cancer and treatment to conduct a complete analysis of cancer.B2M and PTEN are considered potential therapeutic targets that can improve the immune response. “High immune subtype” patients can generally obtain a better immune prognosis effect if TGF-β inhibitors are combined.In summary, this comprehensive study classified cutaneous melanoma skin samples based on immune function and proposed three subtypes according to SING and the tumour microenvironment. Mutations in


Pocillopora and Porites, and investigated whether this technique can benefit coral heat resistance while modifying the bacterial microbiome. Initially, heat-tolerant donors were identified in the wild. We then used fresh homogenates made from coral donor tissues to inoculate conspecific, heat-susceptible recipients and documented their bleaching responses and microbiomes by 16S rRNA gene metabarcoding.Microbiome manipulation could enhance heat tolerance and help corals survive the pressures of ocean warming. We conducted coral microbiome transplantation (CMT) experiments using the reef-building corals, Pocillopora sp.) and sixteen (Porites sp.) donor-specific bacterial species were identified in the microbiomes of recipients indicating transmission of bacteria. The amplicon sequence variants of the majority of these transmitted bacteria belonged to known, putatively symbiotic bacterial taxa of corals and were linked to the observed beneficial effect on the coral stress response. Microbiome dynamics in our experiments support the notion that microbiome community evenness and dominance of one or few bacterial species, rather than host-species identity, were drivers for microbiome stability in a holobiont context.Recipients of both coral species bleached at lower rates compared to the control group when exposed to short-term heat stress (34 °C). One hundred twelve (Our results suggest that coral recipients likely favor the uptake of putative bacterial symbionts, recommending to include these taxonomic groups in future coral probiotics screening efforts. Our study suggests a scenario where these donor-specific bacterial symbionts might have been more efficient in supporting the recipients to resist heat stress compared to the native symbionts present in the control group. These findings urgently call for further experimental investigation of the mechanisms of action underlying the beneficial effect of CMT and for field-based long-term studies testing the persistence of the effect.Video abstractThe online version contains supplementary material available at 10.1186/s40168-021-01053-6. Reef-building corals are subjected to heat stress due to ocean warming. Frequent heatwaves induce coral bleaching, the disruption of the symbiosis between the coral host and its dinoflagellate symbionts. With ongoing ocean warming, coral bleaching events that entail high mortality have increased over the last decades and are expected to intensify , which cPocillopora sp. and Porites sp., from the Andaman Sea in Thailand. First, we assessed heat stress tolerance by employing short-term heat stress assays  in ordei et al. , 36. 16SWe present the results from two coral microbiome transplantation experiments with the underlying concept of using a fresh tissue homogenate of heat-tolerant donors from the wild, containing living microbiome communities, for the inoculation of heat-sensitive conspecifics to enhance their resilience under ocean warming Fig. .Fig. 1CPocillopora and Porites, by screening fragments from wild colonies living in high and low variability reef sites, “LowVar” and “HighVar,” in the Andaman Sea , whereas their “HighVar” conspecifics exhibited no significant response under heat exposure (Tables Sp = 0.051). Yet, the effect of heat exposure on “LowVar” corals was larger compared to the minor effect on “HighVar” conspecifics (effect size ~ −0.4), which hardly showed a bleaching score decline under heat exposure. Furthermore, only Pocillopora fragments showed a differential response between the two sites of origin based on photosynthetic efficiency , showing no difference in the stress response of the dinoflagellate symbionts. Based on these outcomes, corals from the “LowVar” site were designated to be recipients, while the more heat-tolerant “HighVar” corals were used as microbiome donors in the CMT experiments.First, to identify suitable donor corals, we assessed heat stress responses of two coral species, Sea Fig. a-d. We uSea Fig.  A-B and Sea Fig. . Corals Sea Fig. a, b. In  p < 0.00, whereascy Fig. S A-B. Her p < 0.00, whereasp = 0.002, Fig. Porites “I” recipients were not entirely immune to bleaching, as the effect of heat exposure was significant and the bleaching score slightly reduced , suggesting a beneficial effect of CMT on Porites recipients.The two CMT experiments, one for each coral species, consisted of two parts respectively Fig. S C-D: firMeasurements of photosynthetic efficiency did not reflect the beneficial effect of CMT in the same manner as shown by the bleaching score Fig. S E-F. OveSupplementary Materials and Methods; Dataset Sppermanova < 0.001). Source seawater tank communities were remarkably distant to both coral microbiomes, whereas seawater communities of experimental tanks were closer to the respective coral microbiomes  were shared with the seawater microbiomes , Alteromonas sp. (up to 62%), and a species of Rhodobacteraceae (up to 40%) . In few individuals, Alteromonas sp. and a species of Entomoplasmatales were prevalent, but comparably less abundant  were significant between the three sample groups at the experiment start, i.e., inoculum, donor samples from field collection, and recipient samples  and one Halobacteriovorax sp. were most abundant among these exclusive inoculum-specific ASVs, contributing to ~3% of the entire sequenced inoculum bacterial community. Other ASVs (0.1–0.3%) were an α-proteobacterium (Dstr-E11), three unclassified bacteria (uncultured Mollicutes), six Rhodobacteraceae, and five Alteromonadaceae. In Porites, six species of Endozoicomonas sp. were most prominent contributing to 3% of the entire inoculum community. To be considered, the “filt-10” data set represents the pocilloporid inoculum with 904,749 reads and Porites inoculum with only half of that , we find that 146 ASVs were exclusively found in the pocilloporid inoculum, which represent potentially new donor bacteria, not yet present in the recipients’ microbiome prior to CMT Fig. S A. Thirtum Fig. S B when c5 cells ml−1 inside the enclosures and with 1.5 × 104 cells ml−1 once the tubes were removed. Porites recipients were exposed to bacterial densities of 1.9 × 106 (day 1), 1.8 × 106 (day 2), and 1.2 × 106 (day 3) cells ml−1 inside the tubes and 1.7 × 105, 1.6 × 105, and 1.1 × 105 cells ml−1, respectively, when tubes were removed. Due to logistic limitations in the field, we could not perform a dosage test ahead of the experiments. To further develop the CMT method, more testing in this regard should be considered. Follow-up experiments are recommended to adjust bacterial cell densities of inocula prior to inoculation, which will require longer experimental time frames, laboratory space, and coral tissue material, but will allow for measuring dosage-dependent effects.Inoculations were performed in semi-enclosed micro-environments Fig. S, where bPocillopora, but not for Porites  were potentially transmitted through the CMT treatment and may be suspected of helping to establish a more heat-resistant recipient coral phenotype.Probiotics could become a supporting intervention to alleviate the coral reef crisis by helping corals to endure increasing temperature stress through administration of beneficial bacteria . In this5–107 of bacterial cells/mL in bulk and were slightly higher for Porites than for Pocillopora.The first hurdle of performing the CMT was the inoculation procedure which required maintenance of recipients in small volumes of water with limited flow and enriched particle and bacterial loads . This maNext and most importantly, heat exposure following the inoculation treatment revealed a higher bleaching resistance in the recipient group compared to the control group that received a sterile-filtered seawater inoculum , indicating either a mitigation of stress or a delay of the onset of bleaching. This compares well with observations by Rosado et al.  where stAmpoebophilus sp. and Alteromonas sp. in Pocillopora and Endozoicomonas sp. in Porites; among which Candidatus Ampoebophilus is suggested to have co-evolved with the coral holobiont [Endozoicomonas is the most prominent candidate coral symbiont known to the coral microbiome research community [Our inoculations had a beneficial effect on recipients' heat resistance, but did not trigger any large-scale restructuring of the microbiome in neither of the two coral species. The question remains whether large microbiome community changes are required for achieving an alternation of the phenotype. Studies have reported both cases, microbiome differences without measurable signs of phenotype changes or the contrary –43. Indeolobiont  and Endoommunity , 46. Theommunity . Thus, tOur list of transmitted donor-specific bacteria represents some of the potentially new species that were incorporated into recipient tissues or into the mucus after inoculation. Cells that loosely attach to the corals were excluded through thorough rinsing of the samples with sterile-filtered seawater. However, this list merely represents a list of “candidates,” which the 16S rRNA gene marker, the sequencing effort, and our analysis have been able to capture, while it is important to consider that the use of another marker gene region and a deeper sequencing effort could deliver a more accurate picture . In futuPorites recipients, even though they had experienced a longer lasting and repeated inoculation procedure during CMT. We observed a dynamic Pocillopora and stable Porites microbiome in our study. The contrary has been so far reported in few other studies where pocilloporid microbiomes were the most inflexible [Endozoicomonas. Our study demonstrates the contrast between a flexible pocilloporid microbiome against an inflexible and Endozoicomonas-dominated Porites microbiome, providing the insight that flexibility might be determined by the initial bacterial composition, rather than coral host species. In this regard, our results support the notion that community evenness and bacterial species dominance are drivers for microbiome stability in a holobiont context [Bdellovibrio and like organisms “BALOs” [Peredibacter sp. were transmitted to pocilloporid recipients and may have acted as the main drivers of the microbiome changes after inoculation, whereas BALOs were absent in the stable microbiomes of Porites. Noteworthy, BALOs constitute a suitable bacterial group to be considered for microbiome manipulation approaches as already implemented in aqua farming projects [Vibrios [Microbiome analyses in this study taught us new valuable lessons about coral microbiome dynamics and flexibility (see current perspectives in ). Communflexible , 41, whi context . Additio “BALOs” , in the  “BALOs” , 53. In projects , 55. Man[Vibrios .Our study comes from a bacterial microbiome-focused perspective hypothesizing that bacterial community changes and specific taxa can be meaningfully linked with the altered phenotype of recipients . This miIn corals, a bacterial inoculum serving as an additional food source has been debated . Our CMTNematosella [Our study encompasses experiments performed on a short-term schedule including 1–3 days of inoculation treatments and 1–2 days of acute heat stress exposure. To further develop this method for implementation in coral propagation efforts in a reef restoration setting , 63 alonatosella  and a doatosella .sensu [We draw the final conclusion from a microbiome-focused perspective. Approaches that investigate the probiotic potential of microbiome manipulation, such as several previous coral probiotic studies , 31, 67 sensu , 30.Supplementary Material and Methods). They were purposely chosen based on their local environmental differences and implications for coral heat tolerance [Pocillopora sp. (April 2018) and Porites sp. (November 2018) were collected. Both corals represent two distinct coral ecotypes (branching vs. massive morphology) and are abundant and ecologically significant coral species in Thailand [Collection sites were located in the Andaman Sea, Thailand . The “34 °C” treatment was established by ramping temperatures from 29 to 34 °C for 4 h, holding at 34 °C for 5 h (Pocillopora) or 6 h (Porites), and decreasing temperatures to ambient 29 °C within 4 h  and Porites (colony N = 10). Each experiment consisted of two parts: (i) the inoculation phase with two treatment groups, “I”  and “C” , and (ii) the reassessment of heat tolerance resulting in four experimental groups, i.e., “I x 29 °C,” “I x 34 °C,” “C x 29 °C,” and “C x 34 °C.” We designated colonies from the “HighVar” sites to be donors and collected six Pocillopora fragments from the west shore of Racha Island  and 18 Porites fragments from Panwa reef flat . Inocula were prepared 2 h before each inoculation event by homogenizing the tissues of each donor fragment according to established protocols for coral pathogen transmission . Next, PVC tubes  were placed around each coral fragment to create a semi-enclosed microenvironment to which inoculation shots were added [Porites recipients each received three shots repeated every 24 h over 3 days  or 2 h (Porites). Subsequently, PVC tubes were removed, water flow and aeration were switched back on, and tanks were filled up to 40 L, further diluting bacterial densities. After 24 h, a regular seawater exchange (50% twice a day) was continued. Differences between the two inoculation procedures stem from logistic limitations such as availability of coral material. Following the inoculation phase, heat stress tolerance was reassessed in both recipient groups. Heat tolerance assays were performed as described above with a minor modification of exposing Pocillopora recipients at 34 °C for 7 instead of 5 h.Based on the outcomes of the heat tolerance assessment, colonies from the “LowVar” site were designated to be recipients. For the coral microbiome transplantation (CMT) experiments, we collected four fragments per colony of mission  to “6” , recording a minimum and maximum score . Secondest.org, ) using ararecurve (R package vegan v2.5-6). A filtered data set, “filt-10,” was created from the full data excluding rare ASVs with a total read abundance of <10. Details are provided in the Supplementary Materials and Methods and Dataset SCoral and seawater samples were collected at three time points during the CMT experiments, “start” of inoculation, “end” of inoculation, and “end” of heat tolerance reassessment Fig. S C-D. DNAdabestR v0.2.3 6 [nlme v4 3.1-148 and lme4 v1.1-23 package). Where applicable, coral colony genotype was used as a random factor.∆-values of coral response variables  were used for analyses. Effects of (i) temperature treatments (“34 °C” vs. “29 °C”) within the site of origin , (ii) inoculation (“I” vs. “C”), and (iii) subsequent temperature treatment of inoculated recipient corals (“34 °C” vs. “29 °C”) were evaluated using v0.2.3 6  and linephyloseq v1.32.0 and vegan v2.5-6 in R. We compared (i) coral and seawater microbiomes pooled across time points , (ii) coral groups at experiment “start” , (iii) at the “end” of inoculation, and (iv) at the “end” of heat tolerance reassessment. α-diversity metrics were analyzed by dabestR v0.2.3, ANOVA or Kruskal-Wallis, and generalized linear or linear mixed effect models where suitable. Dissimilarities (Bray-Curtis) and homogeneity of variances were tested by PERMANOVA with 9999 permutations using adonis2 and by PERMDISP using betadisper function, respectively. Pairwise tests followed respectively, pairwise.perm.manova or Tukey HSD test through betadisper. The “filt-10” data set was used to create stacked bar plots at the bacterial species level (showing the most dominant species: relative abundance >10%). UpSetR  analysAdditional file 1. Supplementary materials.Additional file 2: Dataset S1. Analysis table of coral response variables. ‘LowVar’ site = Racha Island east shore, ‘HighVar’ site (Pocillopora) = Racha Island west shore, ‘HighVar’ site (Porites) = Panwa reef flat; heat tolerance (HT) assessment treatments: ‘34 °C’ and ‘29 °C’; Inoculation treatments: ‘I’ = inoculation; ‘C’ = sterile-filtered seawater (FSW) control group; n = replicate fragment numbers; mean difference = mean difference between start and end of a treatment; SD = standard deviation; SE = standard error; CI = confidence interval.Additional file 3: Dataset S2. Analysis tables of microbiome data. Count tables are provided for (A) ‘filt-10’ data and (B) rarefied data (subsampled to 4 000 reads). Tables enclose read abundance counts per amplicon sequence variant (ASV), experiment metadata , and SILVA classification. TYPE = sample type; POC = Pocillopora; POR = Porites; SW = seawater. Timepoints include: t1 = start, t2 = end of inoculation, t3 = timepoint of water collection from the source tank during heat tolerance (HT) reassessment, t4 = end of HT reassessment. I = inoculation; C = FSW control group; H = heat exposure treatment 34 °C; A = ambient temperature treatment 29 °C.Additional file 4: Dataset S3. Full table of potentially transmitted bacteria in the (A)Pocilloporaand (B)Poritesexperiment. Amplicon sequence variants (ASVs) exclusively shared between the inoculum and the ‘I’ recipient’ group after inoculation are provided each with their respective SILVA based taxonomy and sequence. Read abundances for each potentially transmitted ASV show its occurrence within the different treatment groups. ASVs are marked in ‘green’, when also detected in the donor samples. Those, also detected in seawater samples, are marked in ‘blue’. ASVs are marked in red, when detected in the ‘I’ recipient group at the end of heat tolerance reassessment .Additional file 5: Dataset S4. Quality control samples and clean-up of microbiome data. Tables show host-origin and contaminant amplicon sequence variant (ASV) sequences that were removed from the microbiome data set prior to downstream analyses. (A) Table shows ASV sequences of host-origin as matched with GenBank (NCBI). (B) Table shows ASVs identified as contaminants using DNA Extraction Kit and PCR blank samples. Stacked bar charts show bacterial community compositions of (C) extraction kit blank samples and (D) PCR blank samples. Additionally, scoring tables for contaminant ASVs are shown.Additional file 6: Dataset S5. Protocol of raw read processing using QIIME2 V2019.7.


Improving the understanding of how a patient’s beliefs, practices, and experiences affect their health may help healthcare practitioners to take into account religious considerations, not only regarding influences on habits but also regarding adherence to medical treatment advice.Approximately 90% of the world’s population is involved in some spiritual/religious practice, and this dimension has a relevant role in life. Many studies demonstrate the associations between spirituality/religiosity (S/R), and physical, mental, and social health. Systematic reviews have indicated positive associations; however, the mechanisms behind religious coping are not fully understood. The present study aimed to examine the role of religious affiliation in general (ordinary) and health-related decisions. A nationwide, population-based, cross-sectional study was conducted in Brazil using a self-administered online survey. How much religious affiliation influences decision making was investigated. A total of 1133 participants were included, who were classified as Catholics (43.9%), Evangelicals (18.7%), spiritualists (12.8%), non-religious (11.9%), and others (12.7%). Most participants (66.5%) believed that their religious affiliations had moderate to high influences on their decisions. Participants rated the influence as high in marriage (62.7%), in donations (60.1%), in volunteering (55%), in friendships (53.9%), and in work (50.5%). Concerning health-related decisions, the influence was rated as high in drug use (45.2%), in accepting medical recommendations (45%), and in smoking (43.2%). The influence of religious affiliation on general decision making was significantly correlated for dietary restrictions ( Approximately 90% of the world’s population is involved in some spiritual/religious practice, and this dimension plays a relevant role in life . EvidencMany studies have demonstrated associations between spirituality/religiosity (S/R) and physical, mental, and social health . SystemaOn the one hand, studies in this field have not been designed to consider patients’ perceptions about religion , and theTherefore, this study aimed to evaluate how much religious affiliation influences daily life and health-related decisions, thereby providing to healthcare providers more information to address religious considerations and demonstrate how a patient’s beliefs, practices, and experiences may affect his/her health.® Panels, one of the main companies offering online instrument services [coalizaointerfe.org, accessed on 10 September 2020), a Brazilian institution composed of representative members of several religious affiliations, and non-religious faith and professional healthcare practices in Brazil. Data were collected between 28 June 2016 and 22 August 2016, through a self-administered online survey. Respondents were invited to participate and complete the online survey, and those who agreed signed an online consent term.This is a nationwide, cross-sectional, quota sampled, self-administrated online survey study. Invitations were sent by Qualtricsservices , for theThe sample size was determined by non-probability quota samples, thereby assuring that distinct subgroups of the population and their characteristics were represented. Quotas were set to limit the respondents according to social class distribution, age, gender, and geographic location, so the population surveyed could meet the same profile of the general adult population in Brazil, according to the 2010 census. A previous article  showed tA question about religious affiliation was asked: “What is the best option below to define your current religious affiliation?” Response options included 16 options: “Catholic,” “Evangelical,” “Kardec Spiritist,” “Jewish,” “Buddhist,” “Umbanda,” “Candomble,” “atheist,” “agnostic,” “spiritualist,” “Christian,” “Jehovah’s Witness,” “Seicho-no-ie,” “Wicca,” “no religion,” and “others.” Due to the limited number of responders in some affiliations, we re-allocated the sample into 6 groups: “Catholics,” “Evangelicals,” “spiritualists” , “other Christians,” “non-religious” , and “other denominations” . Kardec Spiritists and spiritualists supposedly behave similarly. Although “others” seems heterogeneous, their sample size was still small, justifying their being analyzed together.The self-reported influence of religious affiliation on general life was assessed by the question: “How much does religious affiliation influence your decisions?” The self-reported influence of religious affiliation on various attitudes was examined by: “How much does your religious affiliation influence your”: “dating,” “marriage,” “friendships,” “work,” “clothing choices,” “volunteering,” “donations,” and “politics.” The self-reported influence of religious affiliation on health-related attitudes was examined by: “How much does your religious affiliation influence” your decisions regarding “diet,” “alcohol consumption,” “drug use,” “tobacco consumption,” “refusal of medical recommendations,” and “acceptance of medical recommendations”?t-tests for normal samples. The Wilcoxon test was used for non-parametric comparisons, and Fisher and chi-square tests were used to compare proportions (IBM SPSS Statistics version 25). The study followed international ethical regulations (Declaration of Helsinki principles) and was approved by the local Ethics Research Committee of IPq HCFMUSP (CAAE 64956717.4.0000.0065). All participants gave informed consent online.All questions presented 5 alternatives: 1 (very little), 2 (a little bit), 3 (moderately), 4 (quite a lot), and 5 (a lot). Analysis was performed with 95% confidence intervals. For correlations, we used Pearson tests; for comparisons, paired From 1252 participants, 1131 (90.3%) completed the selected questions. The sample was composed of 536 (47.4%) men and 595 (52.6%) women, with a mean age of 40.5; 57.9% of the participants were married and 37.8% had a monthly family income between USS2000.00 .The sample was categorized into six religious groups: Catholics (43.9%), Evangelicals (18.7%), spiritualists (12.8%), other Christians (6.6%), other denominations (6.1%), and non-religious (11.9%). Regarding how much their religious affiliations influenced their decision making, 21.4% of the participants reported “very little,” 12.1% “a little bit,” 23.2% “moderately,” 26.1% “quite a lot,” and 17.2% reported “a lot.”r = 0.530), “marriage” (r = 0.551), “friendships” (r = 0.565), “job” (r = 0.571), “clothing choices” (r = 0.507), “volunteering” (r = 0.568), “donations” (r = 0.590), and “politics” (r = 0.349). Likewise, health-related decisions correlated as follows: “diet” (r = 0.462), “alcohol consumption” (r = 0.458), “drug use” (r = 0.441), and “tobacco consumption” (r = 0.456). “Acceptance of medical recommendations” has a correlation of 0.560. “Refusal of medical recommendations” presented as r = 0.314, demonstrating that the influences of religious affiliation were lower on health-related aspects, as detailed by religious affiliation categories (Religious affiliation correlated with daily decisions to various degrees: “dating” (tegories .Most participants’ (66.5%) believe that their religious affiliations have moderate to high influences on their general decisions. Participants rated the influence of religious affiliation as high on marriage (62.7%), on donations (60.1%), on volunteering (55%), on friendship (53.9%), on work (50.5%), on dating (49.6%), on choice of clothing (42%) and on politics (27.2%) .Concerning health-related decisions, the influence of religious affiliation was high on drug use (45.2%), on accepting medical recommendations (45%), on smoking (43.2%), on alcohol consumption (39.7%), on dietary restrictions (37.1%), and on refusing medical advice (22.6%) .Evangelicals had the highest levels of religious influence within daily life and health-related decisions, and as expected, the non-religious group had the least influence from religion (though they were referring to the influences of beliefs on life decisions).Our data show religious affiliation influences daily life and health-related decisions. Overall, the influence of religious affiliation on general decisions was considered high by the participants, particularly in areas such as marriage, donations, friendships, and work. However, this influence is also considerable in health-related decisions, such as the refusal of medical advice, diet, smoking, and alcohol use. These findings provide further support to the scientific literature, which has been showing that religion is a relevant aspect of individuals’ cultural background , importaHistorically, religions incorporated forms of fasting and self-starvation. Many important religious figures, such as Moses, Buddha, and Jesus abstained from eating as part of ascetic/mystic practices. A controlled trial study found evidence of treatment via spirituality-oriented groups based on the eating attitude test (EAT), and eating disorder specific symptoms, such as binging, purging, restricting, and attitudes about food and dieting . That waStudies have demonstrated a relationship between abstinence and alcohol and use/abuse , but alsFor tobacco consumption, a nationwide study performed in the United Kingdom  indicateConcerning the influence of religion on following or refusing medical advice, one study showed trust in physicians and the health system. A nationwide U.S. study showed a positive association with adherence to treatment and strength of religious affiliation . A case Thus, awareness about the global role of S/R in health has been increasing . HoweverThis study had some limitations that should be considered. First, this was a cross-sectional survey, avoiding inferences about cause and effect. Second, data collection was carried out only for persons 18 years old or older who had online access to email, social media, and websites; it is possible that some groups of the population, such as residents from rural areas, those with lower socioeconomic levels, and older adults, were included at a lower frequency. Finally, we used self-reported measures to investigate the influences of religious affiliation on daily decisions, instead of evaluating their behavior in real-life scenarios. However, previous international studies have already used online surveys to investigate spirituality and religion in the general population  and the In conclusion, religious affiliation influences daily life and health-related decisions to different degrees. Healthcare providers need to consider religious aspects of patients’ lives to consider how a patient’s beliefs, practices, and experiences may affect their health, not only because of religion’s influences on habits such as diet, smoking, drinking, and drug use, but also regarding adherence to medical advice.


A network meta-analysis of randomized controlled trials (RCTs) was conducted to explore the cardiovascular outcomes of all the kind and dosages of sodium-glucose cotransport-2 (SGLT2) inhibitors in type 2 diabetes mellitus (T2DM) patients.The Cochrane Library, PubMed, and Embase databases were systematically searched for studies to compare the therapeutic effects of different SGLT2 inhibitors in T2DM patients. The effect measurements estimate chosen were odds ratios (ORs) and their corresponding 95% confidence interval (CI). Forty-seven RCTs involving a total of 70574 participants were eligible for direct and indirect comparisons. In direct comparison, treatment with dapagliflozin 5mg showed significantly lower risk of all-cause mortality compared with treatment with dapagliflozin 2.5mg . According to NMA, interestingly, empagliflozin 10mg/25mg, and canagliflozin 100mg was associated with significantly lower risks of all-cause mortality compared with placebo . Compared with placebo, dapagliflozin 10mg, empagliflozin 10mg and 25mg displayed the lower risks for cardiovascular events  by direct comparison. Moreover, canagliflozin 100/300mg showed significantly higher risks of cardiovascular events compared with empagliflozin 10mg  and empagliflozin 25mg  according to NMA. There were non-significant differences among all interventions in volume depletion in traditional pairwise meta-analysis. While in NMA, canagliflozin 100/300mg were associated with significantly increased risks of volume depletion compared with placebo .ad hoc RCTs.In the limitations of the NMA, this study showed that empagliflozin might be better than other SGLT2 inhibitors with low risks of all-cause mortality and cardiovascular events in patients with T2DM suggesting the need for  Type 2 diabetes mellitus (T2DM) affects roughly 451 million adults in 2017 worldwide, these figures were expected to increase to almost 700 million by 2045 , the preSodium-glucose cotransport-2 (SGLT2) inhibitors, which reduce blood glucose levels in an insulin-independent manner in T2DM patients , are corNetwork meta-analysis (NMA) offers the potential to assess multiple therapeutic strategies simultaneously within a single framework and to rank treatments based on efficacy and safety . In the We conducted a systematic search up to October 1, 2020, without any language restriction, using PubMed, Embase, the Cochrane Library, and Clinical trials. We searched studies with key words and Medical Subject Headings that covered “diabetic” or “diabetes” or “Type 2 Diabetes Mellitus” or “T2MD” and “sodium-glucose co-transporter 2 inhibitors”, or “SGLT 2 inhibitors” or “SGLT2 inhibitors” or “sodium-glucose transporter inhibitors” or “canagliflozin” or “dapagliflozin” or “empagliflozin” or “ipragliflozin” or “remogliflozin” or “tofogliflozin” or “sergliflozin”. We also reviewed the corresponding reference list of each retrieved article to identify any relevant studies that may be neglected. The meta-analysis was conducted and reported according to the Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) guidelines . The seaWe collected all RCTs to compare the therapeutic effects of different SGLT2 inhibitors in T2MD patients in this network meta-analysis. Inclusion criteria of the studies were as follows: (a) T2MD patients treatment with SGLT2 inhibitors, (b) study design was an RCT of the treatment group (SGLT2 inhibitors) and control group, (c) studies with outcomes of “all-cause death”, “all-cause mortality”, “myocardial infarction”, “nonfatal myocardial infarction”, “nonfatal stroke”, “cardiovascular death”, “hypertension”, “hypotension”, “volume depletion”, “dehydration”, or “hypovolemia”. The detail was shown in the The criteria for exclusion were as follows: (a) studies such as systemic reviews, comments, case reports, conference abstracts, and editorials, (b) subjects with an eGFR level lower than 30 mL/min per 1.73m , and (c)Included trials reported comparisons of 10 interventions . NMA integrates data from direct comparisons of treatments within trials and from indirect comparisons of interventions assessed against a common comparator in separate trials to compare all investigated treatments.Two authors (J-Y and Y-PP) extracted data and accessed quality independently in an electronic database. The investigators cross-checked the data and reached a consensus on any discrepancies through discussion. Disagreements were resolved through discussions or referral to other authors (S-W and W-QH). Reference lists of identified trials and review articles were manually scanned to identify related research references at the same time as indicated in The extracted data included the first author’s name, year of publication, clinical characteristics, HbA1C% level, sample size, the number of males, doses of treatment, control, combined drugs, follow-up duration, the outcomes of all-cause mortality, cardiovascular events, volume depletion. Cardiovascular events included “myocardial infarction”, “nonfatal myocardial infarction”, “nonfatal stroke”, “cardiovascular death”, and “hypertension”.via Deek’s funnel plot asymmetry.Two independent reviewers (J-Y and Y-PP) assessed the methodological quality of included trials using a slightly adapted version of the risk of bias approach by using Review Manager 5.3  risk of bias tool including four sections: selection, performance, detection, attrition, reporting, and other bias. The publication bias assessment was performed The data were abstracted and analyzed by STATA  and Review Manager . The odds ratios (ORs) and their corresponding 95% confidence interval (CI) were used to compare different medications with respect to various clinical outcomes. For each analysis, we generated 50000 simulations for each of the 2 sets of different initial values and discarded the first 20000 simulations as the burn-in period. The stability of the results was obtained by sensitivity analyses by discarding each study sequentially. Convergence was checked using trace plots and the Brooks-Gelman-Rubin . To rank(detail in ). Of 43 studies, all studies reported the end point event of all-cause death, 25 studies submitted data on cardiovascular events, and 30 studies provided data on volume depletion. The number of patients included in every study ranged from 35 to 17160, and the follow-up for patients ranged from 4 to 201 weeks. The risk of bias in studies contributing to the primary outcomes was generally low . According to NMA, interestingly, empagliflozin 10mg/25mg, and canagliflozin 100mg was associated with significantly lower risks of all-cause mortality compared with placebo . Moreover, empagliflozin 10mg/25mg was leaded to significantly lower risks of all-cause mortality compared with dapagliflozin 10mg , as depicted in The comparative effects of different class and doses of SGLT2 inhibitors in reducing mortality by SUCRA probabilities and incidence rate of each intervention was shown in In traditional pairwise meta-analysis, compared with placebo, dapagliflozin 10mg, empagliflozin 10mg and 25mg displayed the lowest risks for cardiovascular events . According to NMA, canagliflozin 100/300mg was associated with significantly higher risks of cardiovascular events compared with empagliflozin 10mg  and empagliflozin 25mg  . The incidence of volume depletion induced by canagliflozin 300mg was significantly higher than that induced by dapagliflozin 5/10mg, empagliflozin 10/25mg and canagliflozin 100mg. These NMA results are illustrated in Canagliflozin 300mg had the highest probabilities of being ranked first with respect to volume depletion (SUCRA 95.5%), whereas canagliflozin 100mg had the second highest probability (SUCRA 75.1%). Both dapagliflozin 5mg and empagliflozin 10mg shown smallest cumulative probabilities for volume depletion, with all values lower 30% , as depicted in Treatment from network meta-analysis evidence in general did not demonstrate evidence of statistical inconsistency . Although the potential factors that responsible for mortality reduction of canagliflozin are need to be further investigated, it may be relevant to identify that canagliflozin has less SGLT2 selectively and may induce more glucosuria , the incubation project of the National Natural Science Foundation of the Second Affiliated Hospital of Nanchang University (No. 2021YNFY2021), the Jiangxi Graduate Innovation Special Fund (No. YC2019-B039), the Jiangxi Provincial Health Commission Project (No. 202210663), and the State Scholarship Fund of the China Scholarship Council (grant number 201906820003).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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