Designing new medical devices with advanced humidity sensors is of great significance for patients with incontinence-associated dermatitis (IAD). The primary goal of this study is to test the humidity-sensing mattress system for patients with IAD in clinical settings. The design of the mattress is set at 203 cm, with 10 × 3 sensors, dimensions of 19 × 32 cm, and a weighted bearing of 200 kg. The main sensors consist of a humidity-sensing film, a thin-film electrode (6 × 0.1 mm), and a glass substrate (500 nm). The sensitivity of the test mattress system showed that the resistance-humidity sensor was at a temperature of 35 °C ( Medical mattresses with advanced humidity sensors are receiving significant attention when it comes to treating patients with IAD ,2,3. Des devices ,5,6. Som devices , skin te devices , metal o devices , transep devices , and wat devices . In the  devices ,13,14, f devices , and the devices .Humidity sensors for patients with IAD have been tested with moisture-associated dermatitis, liquid, and water vapour ,8,10. ThTypically, the traditional design of humidity-sensing mattresses for patients with IAD has limitations, such as early IAD diagnosis ,7. IndeeThus, there still remains a lack of advanced humidity sensors which have been tested with patients exhibiting early signs of IAD. Indeed, the characteristics of sensing moisture-associated skin damage are limited, focusing on different types of sensing materials . PreviouAccordingly, our study has designed a humidity-sensing mattress for patients with IAD following exposure to experimental testing in clinical settings. Firstly, the design of the mattress consists of a humidity-sensing film, a thin film electrode, and a glass substrate. Secondly, the design is also focused on the stability of the humidity sensors , ambient temperature, and adsorption–desorption dynamic cycles. Finally, when testing the response time of 10–120 s with five volts, the magnitude ranged from 1The humidity sensor is real-time monitoring of wetting moisture, water vapour, and vibration urine for converting the data into a corresponding electrical signal;The thin-film electrode array is a method for the fabrication of submicrometer gold on polyester and silicon. The sensor structure consists of a pair of interdigital electrodes and aluminium films on the glass substrate for the thickness (500 nm).When it comes to the sensing design of the mattress environmental chamber (MEC), it tests individual weight-loading support of 200 kg. The MEC consists of a lengthwise, zipped opening to allow mattress placement, as well as a loading array. The design of the testing mattress has a set of 203 cm × 96.5 cm peripheral outlets and a moisture-bearing patient moisture reservoir (PMR). The PMR rests on humidity sensors consisting of 0.28AH), parts per million (PPM), and the dew/frost point (D/F PT). The humidity sensor classifies the mass of water vapour, in grams per cubic metre, and feet (1 grain = AH is the g/3 or ft3). The RH is tested as the ratio of moisture to the maximum level, which gives the temperature and humidity. In the following, RH is equated as:SH) is defined as:SH is the g/SH is the temperature in a unit volume of gas. RH calculates the ratio of AH to SH as follows:A humidity sensor tests the amount of water vapour and temperature . It is wthe water vapour. The PPMv and PPMw are amongst the AH, the D/F is based on the temperature (above 0 °C), and PT is the temperature (below 0 °C). However, the D/F point parameters are the AH.The PPMv is defined as the volume of water vapour in dry gas, the PPMw refers to of voltage (The sensitivity of humidity is determined with the fixed capacity The sensing sensitivity (S) is defined using the following equation:Shimizu et al.  tested tA porous The humidity-sensing mattress is designed for clinical settings: 203 × 96.5 cm, 10 × 3 sensors, and a dimension of 19 × 32 cm . The phyIn the humidity-sensing mattress, the recording functions include system setup, data storage, graphing, and an alarm. Sensitivity is performed using a system calibration with preferences regarding the humidity sensor. Data storage is recorded as historical records and current data. The graphing function allows the patients and their caregivers to observe the recording. The sensor will present a signal on the screen if a hazard over the threshold is detected. The flowchart of the humidity-sensing system is shown in In the warm-up system, with regard to the humidity-sensing mattress platform, there is a connection between ScreenView and the processor . The response time is set at 1 min at 100 Hz on Arduino technical data. Analogue inputs of the Arduino board are used to extract data at FSR400. The mapping of the contact point of the humidity-sensing platform is shown in The testing of long-term bedridden patients with IAD is arranged with 19 volunteers of different temperature and humidity datasets. All volunteers are tested from the same number of patients with different values of BMI and pH index see . To ensuA total of 19 voluntary patients with IAD underwent experimental testing at the Thammasat University Hospital, Thammasat University Rangsit Campus, Pathum Thani, Thailand. All patients provided informed consent to participate in the study. The Human Research Ethics Committee of Thammasat University (Science), Thailand, approved the study project in accordance with compliance with the Declaration of Helsinki, the Belmont Report, CIOMS guidelines, and international practice (ICH-GCP) (COA 032/2566 Project No. 66NU016). The body position regions consist of three sensors in patients with IAD: sensor 1 is the head and neck , sensor 2 is the shoulders (rhomboid major muscles), and sensor 3 is the lumbar spine (spine endpoint), as can be seen in We designed the mattress so that it consists of a humidity sensor on the surface of the substrate and electrodes. A thin-film electrode is built on the glass substrate, which detects thickness at 500 mm. The length and width of the thin-film electrodes are approximately 0.1 mm, with two substracts (10 × 4 mm), as can be seen in The experimental data show that SHT10, DS18B20, and FSR 400 are inputs, based on the mean values of the recorded data. The aqueous solutions of humidity sensors for long-term bedridden patients with IAD are set as LiCI, MgCThis principal part of the sensor is nodulised under a vacuum ranging from 30–100 °C for 30 min, with the voltage signal of 0.85 V for the same RH change. The sensor resistance is extracted from 10 cycles, and the humidity is changed to 5% HR with a 10 s change ratio at a constant temperature of 35 °C. The resistance-humidity characteristics of the sensor are 35 °C, voltage  are repeatedly tested with calibration changes at 0.5% RH, voltage , which achieved 90% of the total impedance change. The sensitivity exhibited a fast response and a recovery time of between 10 s and 30 s, which is the best reported time for a resistive type of humidity-sensing mattress for IAD in clinical settings ,32,37. Ag et al. , Bian etg et al.  and Chu g et al.  fabricatIn conclusion, the design of the humidity-sensing mattress has been tested with regard to the water vapour with RH, AB, PPM, and D/F PT. The testing showed resistance-humidity characteristics of the sensor at 35 °C (The development of the humidity-sensing mattress is a crucial step in the production of a novel piece of medical technology that provides a faster response, high sensitivity, and recovery time; indeed, it may also be a potential design for practical application. Notably, the design of the humidity-sensing mattress compounded with the thin-film electrode as the RH increased to 90%, showing excellent sensitivity. This property enables the sensor to be applied to medical diagnosis for patients with IAD. When the design has been applied, and the enhanced clinical acceptance of sensing material is a reality, it will be possible to provide and develop a low-cost mattress for IAD in clinical homecare. Once available, this humidity-sensing mattress has broad application prospects in the field of flexible sensors, wearable medical diagnostic devices, health detection, etc.


This complex is very stable toward dioxygen due to steric protection of the nickel(II) center. Here, we report the dioxygen reactivity of a new Ni–NO complex, [Ni(NO)(I)(L1″)], with a less hindered N2 type bis(pyrazolyl)methane ligand, which creates a coordinatively unsaturated ligand environment about the nickel center. Here, L1″ denotes bismethane. This complex is also described as a hs-nickel(II) center with a bound 3NO−, based on spectroscopic and theoretical studies. Unexpectedly, the reaction of [Ni(NO)(I)(L1″)] with O2 yielded 2-O2N)(L1″)2](I3) (L3 SNO = 1/2) to 1NO+ , and to NO−  when binding to a transition metal ion, i.e., Mn+–NO·, Mn−1–NO+, and Mn+1–NO−  complex.Nitrogen monoxide (·NO) is a small, relatively unstable, potentially toxic, diatomic free-radical molecule. ·NO has become one of the most studied and fascinating molecules in biological as well as inorganic chemistry ,7,8,9,10Mn+1–NO− ,13. By cMn+1–NO− . In the 6F5)(L1)]  ,16. This1)] − in ), and it1)] − in ,16. We h1)] − in . Later, omplexes ,10 with omplexes , Co 21]6F5)(L1)]omplexes , and Cu omplexes . Using dectively ,21,22. T· ligand ,10,23.10 system, did not show any reactivity toward dioxygen  and [Cu(κ1-ONO)2(L1″)]. The main differences between these complexes relate to the different ligand charges  and bulkiness (tertiary butyl versus isopropyl substituents)  and [CuCl2(L1″)], which again differ for the same reasons mentioned above  (PF6)       , an hs-{NiNO}dioxygen . This isdioxygen   . We alsoed above ,26. Thised above , [Ni(NO)ed above  (L0f− = NO)(L0)] ,29 (L0− n)](PF6)  (iPr3tacmp-tol)]  (Tmp-tolTseMes)]  (TseMes−BuIm)3}]  (HB(tBuIH2Im)3}]  (PhB(CyCMeBz)3}]  (HB(MeBzPhTz)3}]  (HB(p-tB3 group [[Ni(NO)(I)(L1″)] with a less hindered N2 type bis(pyrazolyl)methane coligand to create a coordinatively unsaturated ligand environment. We obtained an unexpected, six-coordinate compound, 2-O2N)(L1″)2](I3)[Ni(L3)], [Ni(NO)(L0f)] is also stable toward dioxygen due to the hindered CF3 group . In this3)(PPh3)2] was reported in 1971 by Professor Enemark , was obtained using [Ni(NO)(Br)(PPh3)2] as the precursor [3)2] with the potassium salt of the ligand [n could also be used for the synthesis [2(I)]2 and [Co(NO)2(I)]n were used to synthesize M–NO complexes such as [Fe(NO)(L3)] [2(L1″)](BF4), and [Co(NO)2(L1″)](BF4) [3)2] and [Ni(NO)(I)]n [n as starting material in this research. The Ni–NO complex [Ni(NO)(I)(L1″)] was obtained by the reaction of [Ni(NO)(I)]n and the ligand L1″, as shown in [Ni(NO)(I)(L1″)], suitable for structural characterization. The coordinated iodide ion is needed for the structural stability of the complex. If we add a THF solution of AgPF6 to a solution of [Ni(NO)(I)(L1″)] to remove the iodide ion, the color of the solution changes from green to colorless, indicating that, upon removing the iodide, the complex decomposes.The first structural characterization of a Ni–NO complex [Ni(NO)(L3)] , [Fe(NO)″)](BF4)  previousNO)(I)]n . Therefo[Ni(NO)(I)(L1″)] is shown in The structure of [Ni(NO)(I)(L1″)] is four-coordinate with three nitrogen atoms from L1″ and NO and the iodide bound. The Ni1–N11 and Ni1–N21 bond lengths (2.0157 (12) and 2.0234 (12) Å) are experimentally equivalent and considerably longer than the Ni1–N1 (1.6467(16) Å) bond. The N1–O1 bond length is 1.136 (3) Å and the Ni1–N1–O1 angle is 172.42(17)°. The presence of the bidentate ligand, with a restricted bite angle, introduces significant distortions in this coordination geometry. Thus, the variation in the N–Ni1–N angles is substantial, with the narrowest angle being 91.41 (5)° for N11–Ni1–N21 and the widest being 123.86 (6)° for N1–Ni–N11. The value of τ4 = [360 – (α + β)/141] = 0.80, where α and β are the two widest angles subtended at the metal center [τ4 in [Ni(NO)(I)(L1″)] is closest to 0.85, which corresponds most closely to a trigonal pyramidal geometry (C3v). In this structure, the three nitrogen donors form the basal  plane. To investigate this further, we calculated the distances between the basal planes formed by three of the coordinating atoms and the nickel center. Here, the distance between Ni1 and the plane formed by N11, N21, and I1 is much longer (1.0817 (3) Å) compared to the other three: 0.4900 (3) Å between Ni1 and the plane formed by N11, N21, and N1; 0.5673 (3) Å between Ni1 and the plane formed by N11, N1, and I1; and 0.5493 (3) Å between Ni1 and the plane formed by N21, N1, and I1. The latter three distances are quite similar. Based on these considerations, the coordination geometry of the complex is distorted tetrahedral, which is a different conclusion than the result from the τ4 value discussion.The coordination geometry of Ni in l center . The val−1 in these compounds, showing a larger degree of variability and indicating distinct differences in the electronic structures of these complexes. Therefore, careful spectroscopic experiments as well as theoretical support are very important to describe the true electronic structure of [Ni(NO)(I)(L1″)], as well as the oxidation state of the metal center and the NO group  were measured using KBr and CsI pellets, respectively (I)]n (−1 in [Ni(NO)(L0f)] [−1 in [Ni(NO)(L3)] [−1 in [Ni(NO)(I)(L1″)], as listed in −1, and is assigned considering related values, 574 cm−1 in [Ni(NO)(L3)] [−1 in [Ni(NO)(L0f)]  [IR and far-IR spectra of ectively . The ν(I)]n . ConsideO)(L0f)]  > 1780 cNO)(L3)]  > 1777 cNO)(L3)]  and 598 O)(L0f)]  (L0f)] .[Ni(NO)(I)(L1″)] are shown in d–d transitions [6F5)(L1)], the band at 804 nm is assigned to the 3T1(F) → 3T1(P) transition, giving rise to a pseudo A signal in MCD (magnetic circular dichroism) because of instate spin–orbit coupling [[Ni(NO)(I)(L1″)] exhibits strong absorption bands in the 500–700 nm range, as shown in d–d transitions of the high-spin Ni(II) center. Therefore, the UV–Vis absorption data indicate that the Ni oxidation number is +II, and that the Ni(II) center is in the high-spin state. This implies that the NO ligand is reduced in the complex to 3NO− (nitroxyl), since the complex charge is zero. This is further discussed in the DFT section. The complex [Ni(NO)(I)(L1″)] has a green color {λmax/nm (ε/M−1cm−1): 492 (130) and 717 (400)}, whereas [Ni(NO)(L3)] {λmax/nm (ε/M−1cm−1): 630 (480)} [λmax/nm (ε/M−1cm−1): 593 (440)} [[Ni(NO)(I)(L1″)] versus [Ni(NO)(L3)]), causing a weaker overall ligand field and a shift of the 3T1(F) → 3T1(P) type d–d transition to lower energy in [Ni(NO)(I)(L1″)] (717 nm) compared to [Ni(NO)(L3)] (630 nm) and [Ni(NO)(L0f)] (593 nm). These spectral features are different from those of the starting material [Ni(NO)(I)]n (UV–Vis spectra (dichloromethane solution and solid state) of nsitions . In [Ni}  and [Ni(3 (440)}  are blueNO)(I)]n .1H and 13C) are compiled in [Ni(NO)(I)(L1″)] has relative sharp 1H-NMR signals in both CDCl3 and (CD3)2CO solution, as shown in [Ni(NO)(I)(L1″)] is +II, and the metal center is in the high-spin state. Therefore, the total spin of the Ni(II) center should be S = 1. However, the NMR spectra clearly indicate that the complex is diamagnetic . This originates from antiferromagnetic coupling between the d-electrons of Ni(II) and the π*-electrons of the nitroxyl ligand . This assignment was previously proposed for other complexes, listed in Nuclear magnetic resonance (NMR) spectra ([Ni(NO)(I)(L1″)], on the other hand, reacts with dioxygen at room temperature ([Ni(NO)(I)(L1″)] and dioxygen are shown in [Ni(NO)(I)(L1″)] slowly reacts with dioxygen. We isolated the product and grew crystals. Crystallographic data of the product show that an unexpected six-coordinate structure was obtained, with the oxidation of 3NO− and I− to NO2− and I3−, as shown in [Ni(NO)(I)(L1″)] decomposed, and L1″ itself was reconstituted. The product complex has a six-coordinate structure with two L1″ ligands bound to the nickel ion and one coordinated NO2−, which originates from the oxidation of 3NO−. The complex is paramagnetic, as evident from 1H-NMR spectroscopy, and therefore contains a hs-Ni(II) center.As mentioned above, the coordinately saturated Ni–NO complexes [Ni(NO)(L3)] and [Ni(NO)(L0f)] do not react with dioxygen. The coordinately unsaturated Ni–NO complex perature . During 2-O2N)(L1″)2](I3)(I3)(I3)[Ni stretches of the coordinated NO2− group (s(N–O) stretch of the NO2− group in [Cu(κ2-ONO)(L3)] was observed at 1264 cm−1 (I3)[Ni] ]  (I3)[Ni(L1″)2](I3) complex using def2-TZVP as the basis set and different functionals. The results are shown in 10, but for other {MNO}x systems as well , we therefore investigated whether the analogous open-shell singlet electronic state could be geometry optimized. Excitingly, using B3LYP we were able to obtain a fully optimized structure of the complex in the BS state. The resulting wavefunction shows spin densities of +1.05 on Ni(II) and −1.19 on the NO− ligand. A superposition of the calculated BS structure and the crystal structure, shown in In these calculations, a closed-shell (CS) electron configuration was used. However, experimentally, the related complex [Ni(NO)(L3)] has been shown to have an open-shell ground state, with a hs-Ni(II) center  . Neverth[Ni(NO)(I)(L1″)] in the BS state is about 2 kcal/mol lower compared to the CS system. Given the similarities between the structural and spectroscopic properties of [Ni(NO)(I)(L1″)] and [Ni(NO)(L3)] and the detailed investigations on the latter complex [[Ni(NO)(I)(L1″)], as observed for [Ni(NO)(L3)]. Attempts to geometry-optimize the complex in the BS state using BP86 were not successful, as the wavefunction always collapsed into the CS state. Comparing the results obtained for the open-shell (BS) and CS systems using the B3LYP functional, we see that for the BS state, the Ni–NO bond distance is longer and ν(Ni–NO) is lower compared to experiment. In contrast, for the CS state, the Ni–NO distance is underestimated and ν(Ni–NO) is overestimated. These results show that the experimental Ni–NO bond strength is in between the predictions for the open-shell and closed-shell system. On the other hand, the Ni–N–O bond angle and the N–O stretching frequency obtained for the BS state are closer to the experimental values. The calculated energy for  complex , these r2-O2N)(L1″)2]+[Ni(I)(L1″)] with O2. In this case, the complex does not involve an antiferromagnetically coupled ground state. For this reason, optimization and frequency calculations were performed using the functional BP86, since it shows the overall best results for the Ni–NO complex. The results from these calculations are shown in In order to assist with the experimental findings, DFT calculations were also performed for the −1, which shift to 1247/1241 cm−1 upon 18O isotope labeling . On the other hand, the antisymmetric N–O stretch of coordinated nitrite is predicted at 1167 cm−1, shifting to 1147 cm−1 with 18O. The experimental value for the N–O stretch is observed at 1201 cm−1, which is right in between those predicted frequencies. However, the experimentally observed isotope shift of 19 cm−1 , and NO gas was purified by passing through a column filled with solid NaOH before the reaction. 18O2 gas was obtained from Shoko Science and was used without any purification . Other reagents were commercially available and used without further purification. The bismethane (L1″) was prepared following a published method  was obtained from crystallographic data by removing the tetrahydrofuran molecule present in the structure. The initial structure for 2-O2N)(L1″)2][Ni [[Ni(NO)(I)(L1″)], we performed both closed-shell and broken-symmetry calculations.Computational studies were performed using Gaussian 16 software . The geof2-TZVP) ,49. The f2-TZVP)  and the f2-TZVP) ; (ii) Bef2-TZVP) , along wf2-TZVP) . For 19H32IN5NiO·0.5(H2O): C 42.89, H 6.06, N 13.16. Found: C 41.94, H 5.87, N 12.77. IR (KBr/cm−1): 2965 s, 2933 m, 2869 s, 1776 vs ν(N–O), 1547 m, 1461 m, 1437 m, 1402 w, 1382 m, 1366 w, 1281 s, 1181 m, 1053 m, 809 m, 796 m. Far-IR : 661 s, 571 m, 543 w, 470 w, 410 w δ(Ni–N–O), 381 m, 329 w, 303 w, 252 w, 212 w, 188 w, 163 w. 1H NMR (CDCl3) δ/ppm (assignment): 1.25 2), 1.40 2), 1.67 2), 2.75 2), 3.83 2), 4.02 , 6.24 . 1H NMR (acetone-d6) δ/ppm (assignment): 1.30 3), 1.47 3), 1.71 3), 3.23 3), 3.85 3), 3.95 , 6.60 . 13C NMR (CDCl3) δ/ppm (assignment): 22.9 (CH(CH3)2), 25.7 (CH(CH3)2), 29.2 (CH(CH3)2), 53.1 (H2C), 100.6 (pz-4C), 152.4 (pz-3C), 164.7 (pz-5C). UV–Vis  λmax/nm (ε/M−1cm−1): 290 (4060), 375 (340), 492 (130), 717 (400). UV–Vis  λmax/nm: 297, 383, 500, 646, 730.Anal. Calcd for C[Ni(NO)(I)(L1″)]  was dissolved in dichloromethane (9 mL) at room temperature in an argon atmosphere. The argon was then replaced with O2 gas and the solution was stirred at room temperature for 3 days. During this time, the color of the solution changed from deep green to brown. Recrystallization from dichloromethane/n-heptane at −30 °C gave brown crystals. Single crystals suitable for X-ray diffraction were obtained by slow recrystallization under the same experimental conditions. Yield: 45% . In a 50 mL Schlenk tube, 38H64I3N9NiO2: C 40.81, H 5.77, N 11.27. Found: C 40.67, H 5.77, N 11.27. IR (KBr)/cm−1(assignment): 3123 w, 2967 vs, 2930 s, 2870 m, 1549 s, 1475 s, 1459 s, 1442 s, 1383 s, 1366 m, 1336 w, 1279 vs, 1201 s(ν(NO2)), 1183 s, 1055 m, 1016 w, 812 w, 661 w. Far-IR (CsI) cm−1: 672s, 662 s, 584 w, 539 m, 508 w, 475 w, 413 w, 391 w, 320 w, 311 w, 228 w, 182 w, 138 vs. UV–Vis  λmax/nm (ε/M−1cm−1): 295 , 365 . UV–Vis  λmax/nm: 301, 376.Anal. Calcd for C18O2 reaction, [Ni(NO)(I)(L1″)]  was dissolved in dichloromethane (5 mL) at room temperature in an argon atmosphere. The argon was then replaced with 18O2 gas and the solution was stirred at room temperature for 3 days. After the reaction, the recrystallization was carried out using the above procedure.For the −1(assignment): 3125 w, 2968 vs, 2931 s, 2870 m, 1550 m, 1473 m, 1459 m, 1441 m, 1385 s, 1366 m, 1335 w, 1280 vs (ν(N18O16O)), 1182 m, 1095 w, 1079 m, 1055 m, 1018 m, 810 m, 661 w.IR (KBr)/cm[Ni(NO)(I)(L1″)] and 2-O2N)(L1″)2](I3) with the less hindered N2 type bis(pyrazolyl)methane coligand L1″, to create a coordinatively unsaturated ligand environment, where L1″ denotes bismethane. The coordination geometry in [Ni(NO)(I)(L1″)] is four-coordinate with three nitrogen atoms from L1″ and NO and a bound iodide anion. We could conclude that the coordination geometry about the Ni center is distorted tetrahedral, based on distances between the basal planes and the metal ion. The ν(N–O) value is 1777 cm−1 in [Ni(NO)(I)(L1″)], which is clearly shifted from ν(N–O) in the starting material [Ni(NO)(I)]n, observed at 1854 cm−1. Moreover, the Ni–NO stretching vibration, ν(Ni–NO), is observed at 572 cm−1. This assignment is based on the consideration of the vibrational frequency of ν(Ni–NO) in related complexes, especially [Ni(NO)(L3)]. Considering the electron-donating properties of hydrotris(pyrazolyl)borate type ligands, the overall electronic structure of the related complexes [Ni(NO)(L3)] and [Ni(NO)(I)(L1″)] is almost the same, in spite of the different coordinating groups (pyrazolyl nitrogen versus iodide anion) and different ligand charges . From the UV–Vis assignments, the Ni oxidation state is +II, and the Ni(II) center is in the high-spin state. This implies that the NO ligand is 3NO− (nitroxyl) in the complex, since the complex charge is zero, which is analogous to the electronic structure reported for [Ni(NO)(L3)]. In comparison, [Ni(NO)(I)(L1″)] has a green color, not blue like [Ni(NO)(L3)]. This difference relates to the different ligand donor set (N3I1 versus N4), causing a shift in the low-energy d–d transitions in [Ni(NO)(I)(L1″)].Previously, we reported a Ni–NO complex with a hindered N3 type coligand, [Ni(NO)(L3)], where L3l)borate . This co[Ni(NO)(I)(L1″)], we obtained an unexpected six-coordinate compound, 2-O2N)(L1″)2](I3)[Ni(I)(L1″)] to O2, which can be attributed to one of the ν(N–O) modes of the bound NO2− group. For the anion I3−, the νas(I–I) band was observed at 137 cm−1, and characteristic strong bands in the UV region of the absorption spectrum were observed at 295 nm  and 365 nm , which are assigned as σ → σ* and π → σ* transitions of I3−, respectively.After dioxygen reaction of [Ni(NO)(I)(L1″)] using both closed-shell and broken-symmetry electronic states were conducted using different DFT methods. Notably, using B3LYP, we were able to optimize the structure of the complex for both of these electronic states, allowing us to make direct comparisons. The results suggest that the complex is best described as a hs-Ni(II) center (S = 1) antiferromagnetically coupled to the 3NO− ligand , with the broken-symmetry state being about 2 kcal/mol lower in energy than the closed-shell state. The electronic structure of [Ni(NO)(I)(L1″)] is therefore analogous to that of [Ni(NO)(L3)] reported previously, in agreement with their very similar structural and spectroscopic properties. DFT calculations for the six-coordinate product complex 2-O2N)(L1″)2]+[Ni(κ were also performed. Our results suggest that the N–O stretching mode of nitrite, observed experimentally at 1201 cm−1, corresponds to the antisymmetric stretch, predicted at 1167 cm−1 with a calculated 18O isotope shift of about 20 cm−1, in agreement with experiment.Theoretical calculations for


The deuterium dose-to-mother (DTM) method measures the human milk intake of breastfed children. Recently, the use of this method has been expanded to classify babies objectively as exclusively breast fed (EBF) or not (non-EBF) based on quantification of non-milk oral water intake (NMOI). However, the calculation of NMOI estimates involves atmospheric temperature and humidity.To evaluate the effects of atmospheric temperature and humidity on NMOI calculation and the classification of exclusive breastfeeding.The effect of indoor temperature and relative humidity on NMOI and the estimated prevalence of non-EBF were examined in two existing data sets of DTM in children by varying temperature in the range of 15 to 35°C and relative humidity in the range of 20 to 80% representing the maximum span of indoor conditions expected. Population-level estimates of NMOI distributions were derived using the rstan package for R v2.21.2.The NMOI decreased at a rate of −1.15 g/day per °C increase and at a rate of −1.01 g/day per percent increase in relative humidity; this was due to variations in non-oral water intake from the atmosphere, a component of the calculation of NMOI, which is dependent on temperature and humidity. For the various locations considered, the mean calculated NMOI varied between 24.6 and 53.3 g/day using the same input data. In the mixed-fed sample of babies, the prevalence of non-EBF based on the earlier defined NMOI cut-off of 86.6 g/day was reduced by 19% when relative humidity was increased by 60%.Atmospheric conditions are essential factors in the computation of NMOI, used in the objective classification of babies as exclusively breast fed or not, and should be considered when the DTM method is used to classify exclusive breastfeeding. The However, assumptions were made in calculating NMOI using the DTM technique . The firTo the best of our knowledge, there have been no systematic evaluations of the influences of atmospheric temperature and humidity on the constants used in the calculation of NMOI. Therefore, in this study we computationally examined the effect of varying atmospheric temperature and relative humidity on calculating NMOI using the DTM method, which in turn is used in the objective classification of babies as exclusively breast fed or not.2.The DTM method of estimating breast milk transfer from mother to baby involves collecting a series of saliva (body water) samples from the mother and baby over two weeks. The DTM method is based on a two-compartment model first described by Coward et al.  as shownbm, kg/day); the fractional water turnover in the mother  and the total water loss in the baby  are estimated. Breast milk intake and Non-Milk Oral Intake estimates are further estimated using these parameters and few assumptions.Four parameters are estimated by minimizing the difference between observed and fitted deuterium enrichment values for mother and baby combined. Parameters namely: Deuterium enrichment in the mother's body water at time zero , the transfer of water from the mother to the baby via breast milk (F2.1.The component of interest in this study was the NMOI (kg/day), which can be estimated from Total water output, Water for growth, Intake of water from breast milk and Non-oral water intake .(1)NMOI=2.2.rcE g/day) was calculated from the rate of efflux (rbE = 0.105 g/min/m2) and body surface area (BSA) (m2).2) of the child is given by n (FRAC) .(2)Fob=FHRexp, %), is 94.6% at temperature of expired air W, kg) (The rate of respiratory water efflux (g/day) was calculated as the product of inspired air volume  and absolute humidity  .IAV=RIA×rtE, g/day)   is given2.3. formula , 10 TBW of a baby is the atmospheric water absorbed through the skin of the baby and the respiratory water influx through the lungs; this was estimated as the product of the proportion of non-oral water intake from the atmosphere (NOWIA) and the total water intake of the baby (rbl- g/day) is calculated as the product of IAV (IAV- L/min) and absolute atmospheric humidity (mg/L)  wasHR(%) is the relative atmospheric humidity, and T(°C) is the atmospheric temperature. The transcutaneous water influx (rcl- g/day) was calculated as 2, HA-absolute humidity (mg/L) ASAT- the atmospheric saturation (mg/L) and BSA (m2) -the BSA of the baby. Therefore, the influx correction wasThe non-oral water intake (the baby .(5)Fa=NOy (mg/L) . rbl=IAVM method . These c2.6.n = 113, body weight 4.0 kg to 7.8 kg) who were observed and verified as EBF  of EBF babies in the Indonesian study was used  , NOWIA iConsequently, the NMOI decreased by −1.2 g/day per °C increase  and relaUsing published average annual indoor temperature and relative humidity across different geographic locations , 13, theThe estimated NMOI (mean and standard deviation) in a sample of 113 EBF Indonesian babies  under va3.2.n = 221) (Under standard IAEA assumptions  and usinn = 221)  were clan = 221) .4.This study examined the effects of atmospheric temperature and relative humidity on calculating NMOI using the DTM method. The assumed NOWIA increased with increasing temperature and relative humidity, resulting in an approximately 1 g/day decrease in the NMOI per unit increase in atmospheric temperature and relative humidity.The DTM technique was initially developed to measure breast milk intake in babies; indeed, the accuracy of the computation of breast milk intake was intact and unaffected by temperature and relative humidity; this reinforces confidence in the technique used to quantify breast milk intake. However, several studies , 15 haveFurthermore, it casts doubt on using cut-off-based deterministic identification of the EBF. The variation in proportion of children classified as EBF based on different temperatures and humidity demonstrates the possibility of misclassification if atmospheric temperature and humidity are not considered in the NMOI. A probability-based approach that assigns the probability of being EBF to every baby based on the distribution of NMOI in the standard EBF population would be better. However, adjustment for atmospheric temperature and relative humidity remains essential to obtain the correct distribution of the NMOI, even when using the probability-based approach. Liu et al.  clearly Atmospheric relative humidity had a more significant impact on the NMOI than temperature. When the relative humidity was increased by 60%, and the temperature was held constant, the prevalence of non-EBF, based on the previously defined NMOI cut-off of 86.6 g/day, was reduced by 19%. Ideally, the cut-off would be constant across geographical locations for the temperature-and relative humidity-adjusted NMOI.To the best of our knowledge, this is the first study that closely examines, although theoretically, the implications of variations in atmospheric conditions on the computation of NMOI, which is becoming an increasingly important output of the DTM technique. However, a simple correction cannot be used to account for variations in temperature and relative humidity in the calculation of NMOI because of the complex calculations involved for NMOI. A web-based, user-friendly application could incorporate the actual atmospheric temperature and relative humidity, thus providing more accurate NMOI calculations. However, this would require a predictable association between meteorological data and indoor atmospheric conditions. This association needs to be understood to easily incorporate these adjustments in the NMOI calculations in the future. The calculation of NMOI can also be affected by the variation in atmospheric temperature and humidity that the baby is exposed to, during the DTM study period of 14 days, and this needs to be explored. To improve the accuracy of the estimation of NMOI, measurement of atmospheric conditions in the baby's immediate environment could be added to future protocols. However, the gain in accuracy must be balanced against the increased complexity of the method in the field as well as in the calculations. A limitation of the study is that the variation in NMOI presented in this paper is a theoretical demonstration and has not been validated in field setting.In conclusion, this study demonstrates the need to consider atmospheric temperature and relative humidity when calculating NMOI.


Immunoparalysis is a compensatory and persistent anti-inflammatory response to trauma, sepsis or another serious insult, which increases the risk of opportunistic infections, morbidity and mortality. Here, we show that in cultured primary human monocytes, interleukin-4 (IL4) inhibits acute inflammation, while simultaneously inducing a long-lasting innate immune memory named trained immunity. To take advantage of this paradoxical IL4 feature in vivo, we developed a fusion protein of apolipoprotein A1 (apoA1) and IL4, which integrates into a lipid nanoparticle. In mice and non-human primates, an intravenously injected apoA1-IL4-embedding nanoparticle targets myeloid-cell-rich haematopoietic organs, in particular, the spleen and bone marrow. We subsequently demonstrate that IL4 nanotherapy resolved immunoparalysis in mice with lipopolysaccharide-induced hyperinflammation, as well as in ex vivo human sepsis models and in experimental endotoxemia. Our findings support the translational development of nanoparticle formulations of apoA1-IL4 for the treatment of patients with sepsis at risk of immunoparalysis-induced complications. A nanoparticle integrating a fusion protein of apolipoprotein A1 and interleukin-4 and that targets myeloid-cell-rich haematopoietic organs resolves immunoparalysis in ex vivo and in vivo models of sepsis. As a result of the immune system’s inability to clear a pathogen, patients with sepsis may experience simultaneous hyper-inflammatory and immunosuppressive characteristics, making this condition extremely challenging to manage4. Up to 30–40% of patients with sepsis show an overriding immunoparalysis phenotype. Immunoparalysis is characterized by a persistent anti-inflammatory innate immune response following an insult such as sepsis5, putting patients at high risk of recurrent and secondary infections, frequently leading to organ dysfunction and death6.Sepsis is a serious medical condition caused by a dysregulated host response to infection that frequently results in organ failure and death8, a process termed ‘trained immunity’10, may be able to reverse tolerance and immunoparalysis induced by exaggerated bacterial stimulation11. Although therapeutically induced trained immunity12 is theoretically a compelling strategy to overcome immunoparalysis, a critical need exists for approaches that can be safely and efficiently translated to clinical settings.Therapeutic strategies to rebalance immune responses in sepsis and to improve patient outcomes through immunotherapy are in their infancy. Recent experimental work suggests that the long-term reprogramming of the innate immune cells15, we discovered that IL4 paradoxically induces trained immunity in addition to its known anti-inflammatory effects. We hypothesized that the unique properties of IL4 could be deployed to overcome immunoparalysis in monocytes induced by stimulation with bacterial endotoxin (lipopolysaccharide (LPS)). However, owing to its unfavourable pharmacokinetic properties and the broad IL4 receptor (IL4R) expression, natural IL4 is poorly suitable for therapeutically regulating myeloid cells in vivo. Routing IL4 directly to the myeloid compartment is therefore an attractive therapeutic avenue. In support of this concept, we developed a fusion protein of apolipoprotein A1 (apoA1)—the main protein constituent of high-density lipoprotein—and IL4 and termed this construct ‘apoA1–IL4’17. The apoA1–IL4 fusion protein readily integrated into lipid nanoparticles to generate myeloid cell-avid IL4 nanoparticles. We then evaluated the behaviour of the IL4 nanoparticles in mice and non-human primates using in vivo positron emission tomography (PET) imaging and ex vivo quantitative gamma counting. Finally, we studied the therapeutic potential of the IL4 nanoparticles in multiple translational inflammation and in vivo and ex vivo models of sepsis.In our quest to simultaneously resolve hyper-inflammation and immunoparalysis, we considered interleukin-4 (IL4) for the modulation of trained immunity and tolerance. When re-evaluating the reported direct effects of this cytokine on monocytes in vitro15. Therefore, we first validated several known inhibitory effects of IL4 on inflammation in primary human monocytes . As expected, IL4 potently inhibited the secretion of the pro-inflammatory cytokines tumour necrosis factor (TNF) and IL6  axis and the signal transducer and activator of transcription 6 (STAT6) signalling pathway19 Fig. . We perf19 Fig. . IL4 tra19 Fig. . In cont19 Fig. . Thus, eIL6 and IL12B that are known to be involved in trained immunity10. Among the prominent attenuated genes were CCL19 and SOCS2, which are important for lymphocyte trafficking and suppression of cytokine signalling, respectively21.To gain insight into the molecular program induced by IL4 training, we performed transcriptomics analysis on naive and IL4-trained macrophages, both before and after LPS re-stimulation on day 6. Overall, 140 genes were more strongly induced (‘upregulated’) in IL4-trained macrophages, whereas 249 genes were attenuated Fig. . Among tWe next performed transcription factor (TF) motif enrichment analysis Fig.  and gene22. Furthermore, we evaluated histone-3-lysine-9-tri-methylation (H3K9me3)-mediated repression of TNF using chromatin immunoprecipitation (ChIP)–quantitative PCR (qPCR) analyses in IL4-induced trained immunity. Using an area under the curve (AUC) analysis of six primer pairs showed a decrease of H3K9me3 in IL4-induced trained immunity, although this did not reach statistical significance 3-9, enhancer-of-zeste and trithorax-domain containing lysine methyltransferase 7 (SET7)  histone methyltransferase inhibitor, abrogated the induction of trained immunity by IL4 Fig. . SET7 hance Fig. . Togethe23 . ApoA1-based nanoparticles (aNPs) inherently accumulate in haematopoietic organs and efficiently target myeloid cells and their progenitors23 Fig. . Specifi23 Fig. . We used23 Fig. , while w23 Fig. . Due to 23 Fig. .Fig. 3EnKD of apoA1–IL4 against the human IL4 receptor alpha (IL4Rα) using SPR to be 4.5 ± 1.1 nM  and HEK-Blue IL4/IL13 (HEK-IL4) reporter cells—were performed to determine the preservation of biological activity after the extraction, purification and refolding process. We determined the equilibrium dissociation constants  nM Fig. . HEK-IL4 nM Fig. . Althoug16. Nanoparticles of different sizes and morphologies were obtained by varying the formulations’ compositions  analysis revealed the expression of IL4Rα (green) on the membrane. Furthermore, binding of bare apoA1, bare apoA1–IL4, aNPs and IL4-aNPs (red) were confirmed by the rim covering the cell surface. When focusing on a zoomed-in section of the membrane, we found that bare apoA1–IL4 and IL4-aNPs were associated with the IL4Rα, forming enriched co-clusters on the cell surface, which we did not observe for bare apoA1 and conventional aNPs Fig. . Togethe89Zr). Note that these experiments were performed with the human variant of IL4 that does not show biologic activity in mice. PET with computed tomography (PET-CT) imaging at 24 h post intravenous administration showed that 89Zr-IL4 and 89Zr-apoA1–IL4 accumulated mostly in the kidney and liver. In contrast, besides accumulating in the liver and kidney, 89Zr-IL4-aNPs accumulated in relatively higher amounts in immune-cell-rich organs, including the spleen and bone marrow . After injection, dynamic PET-MRI  significantly reduced TNF and IL6 production of LPS-stimulated monocytes , Th2 (CD4+ IL4+), Treg cells (CD4+ IL10+), Th17 (CD4+ IL17+) and cytotoxic T cells (CD8+ Granzyme B+ Perforin+) were observed between trained macrophages and controls  to induce immunoparalysis or PBS (as a control). We intravenously administered IL4m-aNPs (200 µg per dose) at 24 h and 48 h after LPS treatment. We re-challenged the mice with another intraperitoneal injection of LPS (0.1 mg kg−1) 72 h after the first challenge  increased serum IL6 concentrations following LPS re-challenge of tolerized mice  due to heterogeneity in the therapeutic response  are characterized by a dysregulated immune response, creating a therapeutic paradox that requires both managing hyper-inflammatory responses and improving host-defence responses against (opportunistic) secondary infections. To take advantage of these features of IL4, we developed a nanoparticle protein-engineering strategy, thereby overcoming this cytokine’s unfavourable in vivo pharmacokinetic properties. Therefore, we trade the reduced IL4 potency of the fusion protein, a characteristic that can be improved in future studies by optimizing the protein and expression system as we did for the chimeric fusion protein, for the benefit of the substantially improved bioavailability and pharmacokinetics. We show that the aNP strategy favourably alters the blood half-life and biodistribution profile of IL4, resulting in an elevated neutrophil-specific and monocyte-specific accumulation in myeloid cell-rich organs such as the bone marrow and spleen, as earlier observed in models of trained immunity32. Furthermore, these studies have shown that aNPs consisting of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), cholesterol and apoA1 do not induce trained immunity, emphasizing that our findings are strictly related to the biological effect of IL4 (ref. 33). While we studied the biodistribution of aNPs containing human apoA1-IL4, we additionally developed the murine variant IL4m-aNP to evaluate in vivo efficacy. Indeed, we show that IL4m-aNPs can partially revert immunoparalysis in an LPS-induced sepsis mouse model. Although the data show restored innate immune responses, with a substantial increase of IL6 production and a clear trend towards increased TNF concentrations in the serum of mice treated with IL4m-aNP, full-blown dose-range-finding studies are required to expand the potential of IL4-aNP therapy in a range of immune-mediated diseases that are characterized by concurrent hyper-inflammation and immunoparalysis. It is encouraging that, using the human fusion protein, we showed that IL4-aNPs can reverse the immune tolerance of cells acquired from a human model mimicking clinical immunoparalysis.The ability of IL4 to simultaneously suppress acute inflammation while inducing a trained immunity program, which has been reported to improve host defence34. Myocardial infarction and stroke are also characterized by sterile inflammation followed by immunoparalysis36, and patients with severe trauma suffer from a similar immune-paralytic condition37. In all these situations, reducing inflammation and overcoming immunoparalysis may be beneficial for patient recovery and preventing secondary infections. IL4-aNP technology might be developed into a therapeutic modality for the treatment of all these conditions.We anticipate that the cytokine-nanoparticle technology may find uses in other myeloid-directed applications. The state of immunoparalysis is not unique to sepsis. Immuno-oncological applications might be considered, because cancer is also characterized by local pro-tumour inflammation and the simultaneous suppression of anti-tumour responses (often mediated by myeloid cells)g was used to separate the peripheral blood mononuclear cell (PBMC) interphase. Following three to five washes with cold PBS, PBMC yield and composition were assessed using a haemoanalyser .Buffy coats (Sanquin) or EDTA whole blood from healthy volunteers was acquired after obtaining written informed consent. The material was diluted at least 1:1 with calcium- and magnesium-free PBS (Lonza) and layered on top of Ficoll-Paque . Density-gradient centrifugation for 30 min at 615 Negatively selected monocytes were obtained using MACS, according to the manufacturer’s instructions . Monocyte yield and purity was assessed on a Sysmex haemoanalyser.6 PBMCs were layered on top of a hyper-osmotic Percoll solution  and centrifuged for 15 min at 580 g, room temperature (RT). The interphase was collected, washed once with cold PBS and re-suspended in RPMI.For some experiments (indicated in the text), monocytes were alternatively enriched from PBMCs by hyper-osmotic density-gradient centrifugation over Percoll (Sigma-Aldrich). About 150–200 × 10−1; Centrafarm). This medium is further referred to as RPMI+++. In addition, 10% (v/v) human pooled serum was added to the medium during cell culture .All primary human monocytes and macrophages were cultured in RPMI-1640 with Dutch modifications (Invitrogen) which was further supplemented with GlutaMAX , sodium pyruvate  and gentamicin  for 24 h with one of the stimuli detailed in Supplementary Table To induce trained immunity in primary human monocytes, a previously optimized and published method was usedFor pharmacological inhibition experiments, the monocytes were pre-incubated for 1 h with one of the inhibitors described in Supplementary Table Following the initial 24 h stimulation, the cells were washed with warm PBS, and warm cell culture medium was added. The monocytes were then allowed to rest and differentiate into macrophages for 5 days. On day 6, the induction of trained immunity was assessed. To this end, the cells were typically re-stimulated with LPS for an additional 24 h to elicit cytokine production. The supernatants were collected and stored at −20 °C until further analysis.g, 4 °C and counted before continuing to downstream applications.For most other trained immunity readout methods, the cells were collected as follows: first, the cells were incubated in Versene cell dissociation reagent (Life Technologies) for 30 min in a cell culture incubator. A cell scraper was then used to remove the cells from the culture plates. To maximize the yield, the culture plates were scraped a second time after adding ice-cold PBS. The macrophages were centrifuged for 10 min at 300 −1) and GM-CSF . The cells were differentiated until day 6, with one medium refresh on day 3. On day 6, the non-adherent cells were collected in addition to the adherent cells (as described above). The moDCs and macrophages were then subjected to analysis by flow cytometry as described below.For experiments in which moDCs were compared to macrophages (untrained control or IL4-trained), moDCs were differentiated as follows. First, negatively selected monocytes were obtained as described above. Following 1 h adherence and a PBS wash, they were cultured in RPMI+++ with 10% HPS, further supplemented with IL4  male volunteers with ages ranging from 18 years to 35 years provided written informed consent to participate in experimental endotoxaemia experiments conducted at the research unit of the intensive care department of the Radboud University Medical Center. All study procedures were approved by the local ethics committee (CMO Arnhem-Nijmegen (Radboudumc), registration numbers NL71293.091.19 and 2019-5730) and were conducted in accordance with the latest version of the declaration of Helsinki.40. In short, participants were admitted to the research unit, and an antecubital vein and radial artery were cannulated to allow administration of fluids and endotoxin, and blood sampling and haemodynamic monitoring, respectively. A 3-lead ECG was recorded continuously throughout the experiment. After iso-osmolar pre-hydration (1.5 l NaCl 0.45% and glucose 2.5% administered intravenously in the hour before the start of endotoxin infusion), volunteers were intravenously challenged with a loading dose of 1 ng kg−1 bodyweight endotoxin (Escherichia coli lipopolysaccharide (LPS) type O113, lot no. 94332B1; List Biological Laboratories), directly followed by continuous infusion of 0.5 ng kg−1 h−1 for 3 h. Participants were monitored for 8 h after the endotoxin loading dose after which they were discharged from the research unit.A continuous endotoxin infusion regimen was used, as is described in detail elsewhereFor this project, blood samples were obtained at two timepoints: 1 h before and 4 h after administration of the loading dose. Negatively selected monocytes were acquired as described above. The cells were adhered and stimulated for 24 h with recombinant human IL4, discoidal IL4-aNPs, LPS  or medium only (as a control). Following a PBS wash, the cells were rested in culture medium for 48 h and re-stimulated with LPS for an additional 24 h. Supernatants were collected and stored at −20 °C.−1), lactate oxidase (2 U ml−1), Amplex red ) was added, and the reaction mixture was incubated for 20 min in the dark at RT. Immediately thereafter, fluorescence was measured at 530/25 nm and 590/35 nm. Gen5 software  was used in conjunction with Microsoft Excel to calculate cytokine and lactate concentrations in the original samples.TNF, IL6 and IL1Ra were measured in cell culture supernatants using duoset ELISA kits (R&D Systems), according to the manufacturer’s instructions. For lactate measurements, a fluorometric assay was used. About 30 µl sample, medium control or known standard was added to a black 96-well plate. Then, 30 µl reaction mix ).Macrophages were collected as described above and transferred to a V-bottom 96-well plate for staining. The cells were centrifuged at 400 Fc-receptors were blocked by incubation in PBS supplemented with 10% human pooled serum for 15 min at 4 °C. After washing once more, surface markers and viability were stained in a volume of 50 µl for 30 min at 4 °C, using the antibodies and viability dye described in Supplementary Table −1) + ionomycin (0.5 µg ml−1) for 4 h in the presence of 100 ng ml−1 Brefeldin A, a ‘golgi plug’. The cells were collected and split over two flow-cytometry antibody panels  at an MOI of 1:5. The cells were washed two times with ice-cold PBA and kept on ice to halt the phagocytosis. The cells were stained for CD45 , and the cells were incubated for 1 h at 37 °C in ambient CO2 levels. Oxygen consumption rates and extracellular acidification rates were measured as proxies for glycolytic and mitochondrial metabolism, using a Seahorse XF Glycolysis Stress Test kit or a Seahorse XF Cell Mito Stress Test kit .Macrophages were collected as described above. The cells were re-suspended in RPMI+++ and seeded into overnight-calibrated cartridges at 10Monocytes or macrophages were lysed in RLT buffer (Qiagen) and stored at −80 °C. RNA extractions were performed using RNeasy mini columns (Qiagen) with on-column DNAse I treatment . Preliminary quality control and measurements of concentration were performed using a Nanodrop apparatus. Samples were sent to the Beijing Genome Institute (BGI Denmark) for RNA sequencing using the DNBseq platform.41. Quantification of gene expression levels as RPKM was performed using MMSEQ (v1.0.10)42. Reads and transcripts were normalized using DEseq2, and pair-wise comparisons were performed. Differentially expressed genes were identified using DEseq2 (v1.34.0) with fold change >2 and P < 0.05, with a mean RPKM >1 (ref. 43). To identify genes that were upregulated or attenuated by IL4 training, RPMI-d6 and IL4-d6 macrophages were compared with RPMI-d6+LPS and IL4-d6+LPS samples, respectively. Gene lists were merged and ranked on the basis of IL4-d6+LPS/RPMI-d6+LPS. Gene ontology and TF motif analysis was performed on gene promoters using the HOMER findMotifs tool (v4.11)44.To infer gene expression levels, RNA sequencing reads were aligned to hg19 human transcriptome using Bowtie (v1.2)6 cells per ml in lysis buffer ), sonicated  and centrifuged .Macrophages were collected as described above and re-suspended in RPMI+++. The cells were fixed for 10 min in 1% methanol-free formaldehyde. The reaction was then quenched for 3 min by adding 125 mM glycine. The fixed cells were washed three times with ice-cold PBS, lysed at approximately 15 × 10−1 proteinase K (Qiagen)) for 1 h at 65 °C and run on a 1% agarose gel to confirm target fragment size of 200–800 bp.Aliquots of chromatin were de-crosslinked in 0.5× TBE buffer , and 1 µg of ChIP-grade antibody (Diagenode) was added. The samples were rotated overnight at 4 °C.3, 1% SDS, in Milli-Q) for 20 min, at RT. Input samples were diluted 12 times in elution buffer. After addition of NaCl (0.2 M) and proteinase K (0.1 mg ml−1), all samples were decrosslinked for at least 4 h on a shaking heatblock . MinElute PCR purification columns (Qiagen) were used to purify DNA fragments. DNA fragments were stored at 4 °C until downstream analysis by qPCR.Magnetic protein A/G beads (Dynabeads) were washed two times in dilution buffer supplemented with 0.15% SDS and 0.1% BSA. The washed beads were added to the ChIP samples and rotated at 4 °C for 1 h. The bead-bound chromatin was subsequently washed  as follows: once with low-salt washing buffer , two times with high-salt washing buffer  and two times with no-salt washing buffer . Chromatin was eluted from the beads in elution buffer  supplemented with 100 µg l−1 ampicillin and grown at 37 °C. At the point that absorbance at 600 nm reached >1.5, 1.0 mM isopropyl β-d-thiogalacopyranoside was added to induce pET20b(+)apoA1–IL4 expression, and cells were incubated overnight at 20 °C. Cells were collected by centrifugation before preparation of lysates and purification.ClearColi BL21 (DE3) (Lucigen) were transformed with a pET20b(+)apoA1–IL4 expression vector. Transformed bacteria were inoculated in 40 ml lysogeny broth (Sigma-Aldrich) supplemented with 100 μg lg and 4 °C for 10 min. Collected cells were re-suspended in PBS and centrifuged at 3,500 g and 4 °C for 15 min. Cells were lysed using 20 ml BugBuster Protein Extraction Reagent (Merck) and 20 µl Benzonase nuclease (Merck) per litre culture on a shaker for 30 min at RT. Cell lysates were centrifuged at 39,000 g and 4 °C for 30 min. Insoluble pellets were washed with 10 ml BugBuster per litre and centrifuged at 39,000 g and 4 °C for 20 min. Pellet containing inclusion bodies was re-suspended in extraction buffer  and incubated on a shaker for 15 min at RT. The suspension was centrifuged at 39,000 g and 4 °C for 30 min to remove insoluble fraction. Filtered soluble fraction was loaded on a nickel column and washed with 15 column volumes IMAC wash buffer. ApoA1–IL4 was unfolded and refolded on the nickel column using a linear gradient unfolding buffer 60 ml  to refolding buffer 60 ml  at 2.5 ml min−1. Refolded apoA1–IL4 was eluted from the column with 0.5 M imidazole, 20 mM Tris and 0.5 M NaCl at pH 7.9. Eluate was collected, concentrated and further purified and buffer-exchanged via size exclusion chromatography  equilibrated with PBS storage buffer. Fractions were analysed by SDS–PAGE, pooled, concentrated and snap-frozen in liquid nitrogen before storing at −80 °C. ApoA1–IL4 mass was confirmed by Q-ToF LC-MS (WatersMassLynx v4.1), using MagTran V1.03 for MS.ApoA1–IL4 fusion protein expressing ClearColi cells were collected by centrifugation at 10,880 m, packaging pCMVR8.74 and envelop pMD2.G in Opti-MEM (GIBCO) at 37 °C for 24 h. Cells were washed with DMEM supplemented with 2% heat inactivated FBS and incubated for 48 h. To obtain the lentivirus containing pHR-apoA1–IL4m, supernatant was centrifuged at 875 g to remove cell debris filtered through 0.45 µm PES syringe filter and centrifuged at 50,000 g for 2 h at 4 °C. Pellet containing pHR-apoA1–IL4m lentivirus was re-suspended in culture medium, snap frozen in liquid nitrogen and sorted at −80 °C. HEK293F cells were transduced with pHR-apoA1–IL4m containing lentivirus in transfection medium  for 24 h. Subsequently, cells were cultured in expression medium (50% EX-CELL 293 Serum-Free Medium for HEK293 Cells (Merck) and 50% FreeStyle 293 Expression Medium (Thermo Fisher Scientific), supplemented with Glutamax, 1% Pen-Strep and 1 µg ml−1 doxycycline (Merck) on a shaker at 150 r.p.m. for 3 days at 37 °C. Culture supernatant containing apoA1–IL4m was centrifuged at 3,500 g, 4 °C for 15 min and filtered through 0.22 µm PES syringe filter to remove cell debris. Filtered soluble fraction was loaded on a StrepTactin XT 4flow 5 ml column (Cytiva) and washed with 5 column volumes W-buffer  with flow rate 1–2 ml min−1. ApoA1–IL4m was eluted from the column with W-buffer supplemented with 50 mM biotin. Eluate was collected, concentrated and snap-frozen in liquid nitrogen before storing at −80 °C. ApoA1–IL4m mass was confirmed by Q-ToF LC-MS (WatersMassLynx v4.1), using MagTran V1.03 for MS.HEK293T cells were co transfected with fuGENE (Promega) including transfer vector pHR-apoA1–IL4To confirm fusion of apoA1 and IL4, 100 ng IL4 (BioLegend), apoA1 and apoA1–IL4 were loaded on a 4–20% polyacrylamide gel (Bio-Rad). After gel electrophoresis, samples were transferred to nitrocellulose membranes with blot buffer . Subsequently, membranes were incubated with blocking buffer ) overnight at 4 °C. The blots were incubated with primary monoclonal antibodies monoclonal anti-IL4  and anti-apoA1  for 1 h at 4 °C. After incubation with primary antibodies, membranes were washed and incubated with rabbit anti-mouse IgG (H+L)–HRP conjugate . HRP-conjugated secondary antibodies were detected with TMB (Thermo Fisher Scientific) and visualized using the Image Quant gel imager .2 dilution concentration series consisted of apoA1–IL4 ranging from 200 nM to 6.25 nM and of human IL4 ranging from 20 nM to 0.65 nM. All samples were prepared in HPS-EP buffer  P20 pH 7.4). Association was monitored for 180 s and dissociation for 180 s with a flow rate of 30 μl min−1. Sensor chip was regenerated with glycine 1.5 . Kinetics was determined by fitting the interaction SPR data for 1:1 binding.SPR measurements were performed using a Biacore ×100 SPR system . Human IL4 receptor alpha-FC chimera (Biolegend) was immobilized on a protein G sensor chip . Log4 cells was added per well in a 96-well-plate. Subsequently, 20 μl stimulus or vehicle was added, and cells were incubated for 20–24 h at 37 °C. Subsequently, 180 μl QUANTI-Blue was added per well to a separate 96-well-plate (flat-bottom), and 20 μl of the cell supernatant was added. The plate was incubated for 1–3 h at 37 °C, and absorbance at 640 nm was measured on a Tecan Spark plate reader to determine SEAP levels.HEK-Blue IL4/IL13 cells were purchased from InvivoGen. This cell line has a fully active STAT6 pathway and carries a STAT6-inducible SEAP reporter gene. The HEK-Blue IL4/IL13 cells produce SEAP in response to IL4 and IL13. The levels of secreted SEAP can be determined with QUANTI-Blue (InvivoGen). About 180 μl DMEM with 10% FBS and 1% Pen-Strep containing 5 × 10−1) in chloroform, DMPC (133.5 μl) and cholesterol (Sigma-Aldrich) (7.5 μl), and for spherical aNPs, POPC (66.5 μl), PHPC (17.5 μl), cholesterol (4.5 μl) and tricaprylin (Sigma-Aldrich) (2.79 μl from 0.956 g ml−1 stock) were combined in a glass vial and dried under vacuum. The resulting film was re-dissolved in an acetonitrile and methanol mixture . For formulation based on apoA1, cholesterol (15 μl) was used. Separately, a solution of apoA1 protein in PBS , apoA1–IL4 protein in PBS  or apoA1–IL4m in PBS  was prepared.All phospholipids were purchased from Avanti Polar Lipids. Four different aNPs were formulated. For discoidal aNPs from stock solutions  was added, and the solution was concentrated to 5 ml; this was repeated twice. The washed solution was concentrated to approximately 1.5 ml and filtered through a 0.22 μm PES syringe filter to obtain the finished aNPs. Protein concentration in aNP samples was quantified with the Pierce BCA Protein Assay Kit (Thermo Fisher Scientific). To formulated fluorescent aNPs, 0.5 mg of DiOC18(3) dye (DiO) (Thermo Fisher Scientific) was dissolved in the chloroform solution used to prepare the lipid film.Both solutions were simultaneously injected using a microfluidic pump fusion 100 (Chemyx) into a Zeonor herringbone mixer  with a flow rate of 0.75 ml minObtained aNP formulations in PBS were filtered through a 0.22 µm PES syringe filter and analysed by DLS on a Malvern Zetasizer Nano ZS analyser. Values are reported as the mean number average size distribution.−1 in DMSO) for 2 h washed three times using a 10 kDa MWCO Vivaspin tubes to remove any unreacted DFO-p-NCS. For radiolabelling, DFO coupled proteins and aNPs were incubated with 89Zr at 37 °C using a thermomixer at 600 r.p.m. for 1 h and washed three times using 10 kDa MWCO Vivaspin tubes to remove any unreacted 89Zr.IL4, apoA1–IL4 and IL4-aNPs were incubated with two molar excesses of DFO-p-NCS (5 mg ml−2 s−1) or 24,000× magnification (dose rate of 11.8 electrons A−2 s−1) and 1 s acquisition time.First, the surface of 200-mesh lacey carbon supported copper grids (Electron Microscopy Sciences) was plasma treated for 40 s using a Cressington 208 carbon coater. Subsequently, 3 ml of IL4-aNPs sample (~1 mg protein per ml) was applied on a grid and vitrified into a thin film by plunge vitrification in liquid ethane by using an automated robot (FEI Vitrobot Mark IV). Cryo-TEM imaging was performed on the cryoTITAN (Thermo Fisher Scientific), equipped with a field emission gun, a post-column Gatan imaging filter (model 2002) and a post-GIF 2k × 2k Gatan CCD camera (model 794).The images were acquired at 300 kV acceleration voltage in bright-field TEM mode with zero-loss energy filtering at either 6,500×  for a few minutes before and during the imaging. The acquisition was performed in total internal reflection fluorescence mode, using ONI Nanoimager (ONI). It is equipped with a 100×/1.4NA oil immersion objective and a sCMOS camera, and in this study, 488 nm (200 mW) and 640 nm (1000 mW) lasers were used. About 10,000 frames were acquired with a 10 ms exposure time with the field of view of 50 × 80 µm. Raw data were processed using the ThunderSTORM software (v1.3)47, yielding images with a spatial resolution of 10 nm.Human monocytes were isolated from a healthy donor’s peripheral blood as described above. About 100,000 monocytes were seeded per well on a cell-culture-treated chambered coverslip . After 2 h of incubation at 37 °C (cell attachment), the cells were incubated for 2 h at 37 °C with Cy5-labelled variant of either bare apoA1 or apoA1–IL4, discoidal aNPs or IL4-aNPs, and spherical aNPs or IL4-aNPs. Subsequently, the cells were washed with PBS and fixed with 4% PFA for 20 min. IL4 receptor was stained with a polyclonal rabbit IgG1 anti-human IL4R  primary antibody for 24 h at 4 °C, followed by a goat anti-rabbit Alexa Fluor 488-conjugated secondary antibody  for 1 h at room temperature. The stained cells were stored in PBS at 4 °C. For the dSTORM, the cells were immersed in GLOXY imaging buffer (40 μg mlMacaca fascicularis) were used, aged 15 years and 16 years. All animals were co-housed in climate-controlled conditions, respectively, at 20–24 °C, 45–65% humidity with 12 h light–dark cycles and provided water ad libitum. Mice were fed a standard chow diet, and non-human primates were fed Teklad Global 20% Protein Primate Diet. Animal care and experimental procedures were based on approved institutional protocols from the Icahn School of Medicine at Mount Sinai. All mice were randomly assigned to experimental groups.Female C57BL/6 J mice (approximately 8–11 weeks old and approximately 20 g) were purchased from Charles River Germany. For non-human primate studies, two male cynomolgus monkeys , apoA1–IL4 (30.1 ± 0.9 μCi), discoidal IL4-aNPs (146.1 ± 46.5 µCi) and spherical IL4-aNPs (108.6 ± 16.9 μCi). Two non-human primates were injected with discoidal 89Zr-labelled IL4-aNPs (1079 μCi and 682 μCi). At predetermined time points, 1, 2, 5, 10 and 30 min and 1, 2, 4, 8 and 24 h for mice and 5, 30 and 90 min and 48 h for non-human primates, after injection blood was drawn and weighed, and radioactivity was measured using a Wizard2 2480 automatic gamma counter (Perkin Elmer). Data were corrected for radioactive decay, and percentage of injected dose per gram of blood (%ID per g) was calculated. Data were fitted using a nonlinear two-phase decay regression in GraphPad Prism, and weighted blood half-life was calculated via the equation (% fast × t1/2 fast + % slow × t1/2)/100. Biodistribution in mice was determined 24 h post injection. After PBS perfusion, tissues of interest were collected and weighed, and radioactivity was measured using a Wizard2 2480 automatic gamma counter (Perkin Elmer). Data were corrected for radioactive decay, and percentage of injected dose per gram of tissue (%ID per g) was calculated.C57BL/6 mice were intravenously injected with 89Zr-labelled IL4 variants, respectively, IL4 (53.6 ± 6.6 μCi), apoA1–IL4 (30.1 ± 0.9 μCi), discoidal IL4-aNPs (146.1 ± 46.5 μCi) and spherical IL4-aNPs (108.6 ± 16.9 μCi). After 24 h, mice were anaesthetized using 1.0% isoflurane in O2 at a flow rate of ∼1.0 l min−1. PET-CT scans were acquired using a Mediso nanoScan PET-CT (Mediso). A whole-body CT scan was executed  followed by a 20 min PET scan. Reconstruction was performed with attenuation correction using the TeraTomo 3D reconstruction algorithm from the Mediso Nucline software v3.04.020.0000. The coincidences were excluded by an energy window between 400 keV and 600 keV. The voxel size was isotropic with 0.4 mm width, and the reconstruction was applied for four full iterations, six subsets per iteration.C57BL/6 mice were injected intravenously with Tissues were placed in a film cassette against a phosphorimaging plate  at −20 °C to determine the radioactivity distribution. The plates were read at a pixel resolution of 25 mm with a Typhoon 7000IP plate reader .For cellular specificity, mice were intravenously injected with DiO-labelled IL4-aNPs that was allowed to circulate for 24 h. Subsequently, mice were killed, and single cell suspensions were created from blood, spleen and bone marrow as previously described. Cell suspensions were incubated with anti-CD115, anti-CD11b, anti-Ly6C, anti-Ly6G, anti-CD19, anti-CD45, anti-CD11c, anti-CD3 and anti-F4/80. Live or dead Aqua was used as viability stain. Cells were subsequently washed and re-suspended in FACS-buffer. All data were acquired on an Aurora 5 l flow cytometer (Cytek Biosciences). DiO-IL4-aNPs were detected in the FITC channel.−1) and dexmedetomidine (0.0075–0.015 mg kg−1). Non-human primates were injected with 1.114 mCi and 0.682 mCi discoidal 89Zr-labelled IL4-aNPs, at a dose of approximately 0.1 mg kg−1. Dynamic PET imaging as performed for 60 min following infusion, and additional static PET-MRI scans were performed at 1 h and 48 h after injection. Furthermore, blood was drawn during imaging at 5 min, 30 min and 120 min after injection. PET and MRI images were acquired using a 3T PET-MRI system . Beginning concurrently with the injection of aNPs, dynamic PET imaging was performed using one bed position covering the chest and abdomen. MR imaging parameters were as follows: acquisition plane, coronal; repetition time, 1,000 ms; echo time, 79 ms; number of slices, 144; number of averages, 4; spatial resolution, 0.5 × 0.5 × 1.0 mm3; and acquisition duration, 42 min and 42 s. After dynamic PET image acquisition, static whole-body PET images were acquired from the cranium to the pelvis, using 4 consecutive bed positions of 15 min each. Simultaneously with each bed, MR images were acquired as described above, except using only 1.4 signal averages, number of slices 160 and spatial resolution 0.6 × 0.6 × 1.0 mm3 . Whole-body PET and MR imaging was also performed at 48 h after injection, using 4 PET bed positions of 30 min each, with MR parameters as follows: acquisition plane, coronal; repetition time, 1,000 ms; echo time, 79 ms; number of slices, 224; number of averages, 2; spatial resolution, 0.6 × 0.6 × 1.0 mm3; and acquisition duration, 29 min and 56 s. Whole-body MR images from each bed were automatically collated together by the scanner. After acquisition, PET raw data from each bed were reconstructed and collated together offline using the Siemens proprietary e7tools with an ordered subset expectation maximization algorithm with point spread function correction for 3 iterations and 24 subsets. Also, Gaussian filter of 4 mm was applied to the images. A three-compartment  attenuation map was used for attenuation.After overnight fasting, non-human primates were anaesthetized using ketamine  were drawn on tissues of interest including spleen, liver, kidneys, lungs, heart, cerebellum and cerebrum, which were traced in their entirety, and bone marrow uptake was determined using three vertebrae in the lumbar spine. For each ROI, mean standardized uptake values (SUVs) were calculated. Discoidal −1 body weight LPS. At 24 h and 48 h, mice were treated intravenously with either 200 µg IL4m-aNPs or PBS. Subsequently, mice were re-challenged with intraperitoneal 0.1 mg kg−1 LPS injection at 72 h. After 90 min, mice were killed, blood was collected for ELISA and single cell suspensions were created from blood, spleen and bone marrow as previously described. For staining protocol, blood samples for ELISA were allowed to clot at RT for 30 min. Serum was taken after centrifugation at 1,000 g for 10 min at 4 °C. Mouse TNF and IL6 ELISAs (Biolegend) were performed according to manufacturer’s protocols. Animal care and experimental procedures were based on approved institutional protocols from the Nijmegen Animal Experiments Committee.For in vivo tolerance model, 11-week-old female C57BL/6 mice were intraperitoneal tolerized with 0.1 mg kgn is indicated in the figure legend. Unless otherwise indicated, statistical analyses were performed in Graphpad Prism . For trained immunity and acute stimulation experiments with primary human monocytes , Wilcoxon signed-rank tests were used. Statistical methods for RNA-sequencing analysis are described above. Two-sided P values under 0.05 were considered statistically significant.Data are shown as mean ± s.d., unless otherwise indicated. Individual data points in graphs are biological replicates, not technical repeats. The number of data points can be clearly discerned in each figure or Further information on research design is available in the Supplementary InformationSupplementary Tables 1–5, and unprocessed SDS–PAGE gels and western blots for Fig. 3.Reporting Summary


Intertrochanteric femoral fractures are commonly treated with intramedullary nails (IMNs). A tip–apex distance (TAD) of more than 20–25 mm is associated with an increased risk of cut-out. The Stryker Adaptive Positioning System (ADAPT) is a computer-assisted navigation system designed to reduce TADs. We aim to assess if the ADAPT reduces the number of outliers with a TAD > 20 mm. All patients with intertrochanteric fractures treated with an IMN between 1 September 2020 and 12 March 2022 were included. Patients were included in three periods: a pre-ADAPT period (55 patients); an ADAPT period (50 patients), where it was compulsory to use the system; and a post-ADAPT period after the discontinuation of the system (59 patients). The TADs and lag screw protrusions beyond the lateral cortex were measured. The median TADs in the three periods were 17.0 mm (8–31 mm), 15.5 mm (9–30 mm), and 18.0 mm (11–32 mm), respectively. The absolute number of outliers with a TAD > 20 mm decreased from 15/55 patients in the pre-ADAPT period to 11/50 patients during the ADAPT period. This observation was not statistically significant, but this is likely due to the lack of power of the present study to show changes of this magnitude. However, our expectation that the ADAPT would diminish outliers markedly or close to zero outliers was not met, as we observed 11/50 = 22% outliers with a TAD > 20 mm when using computer-assisted surgery, i.e., ADAPT and Gamma3 for intertrochanteric fractures. Based on these findings, the use of the ADAPT was discontinued at our level 1 trauma center. Intertrochanteric fractures are among the most common fractures requiring surgery worldwide. The incidence in the US elderly population is approximately 350/100,000 inhabitants yearly . One of Previous studies on the ADAPT have shown promising results in terms of reducing the TAD, operating time, fluoroscopy time ,7,8,9,10The primary aim of this study was to assess whether the use of ADAPT entirely prevents or markedly reduces the number of outliers (TAD > 20 mm), when used in a clinical setting. A secondary aim was to assess whether the use of ADAPT reduces the lateral protrusion of the lag screw, the median TAD, the use of fluoroscopy, and duration of surgery.In this prospective trial of the ADAPT system, all patients admitted to Aarhus University Hospital with AO type 31A2-31A3 intertrochanteric fractures were included in the period 1 September 2020–12 March 2022. To account for a potential learning period, we chose to have three periods: a pre-ADAPT period, an ADAPT period, and a post-ADAPT period. We planned to include approximately 50 patients in each period. Prior to the study, we agreed that if the ADAPT system could not reduce the number of outliers with a TAD > 20 mm after being used 50 times, we would discontinue its use in our department.In the first period, the pre-ADAPT period (1 September 2020 to 27 February 2021), patients were operated on with the Stryker Gamma3 Hip Fracture Nailing System using the technique as described by the manufacturer without the use of computer assistance. In the following ADAPT period, 1 March 2021 to 30 September 2021, the ADAPT 2.1 system was introduced in our department, and it was mandatory for all surgeons to use the ADAPT system when nailing intertrochanteric hip fractures. The post-ADAPT period, 1 October 2021 to 12 March 2022, resembled the pre-ADAPT period, i.e., no ADAPT was available. In the pre- and post-ADAPT periods, we used regular equipment for intramedullary nailing with the Stryker Gamma3 intramedullary nail.The following data were recorded for all patients in a database using Epidata v4.6.0.6 : age, seThere were no exclusion criteria as all patients treated with a Gamma3 nail were considered eligible for operation using the ADAPT system.All patients were scheduled for a three-month follow-up visit in the outpatient clinic, including a clinical examination and radiographic control.The primary outcome was the number of outliers, defined as a TAD > 20 mm and a TAD > 25 mm. The secondary outcomes were the lateral screw protrusion , median The TAD was measured based on perioperative fluoroscopy images using the method described by Baumgaertner et al. , where tMore than 6 months after the last patient was included, we reviewed the patients’ medical files to determine the re-operation rate. We identified the cause of failure, indication for re-operation, and type of re-operation. The number of outliers with a TAD > 20 mm and >25 mm was compared between groups with a Chi square test. The median TAD and lag screw protrusion were analyzed using the Kruskal–Wallis test for non-parametric data with Dunn’s multiple comparison test. Data are presented as the median  or absolute numbers (%). Prism 9.4.1 for macOS was used for the statistical analyses and graphs.The Regional Ethical Committee was consulted prior to commencing this study but stated that as the ADAPT system was introduced in our department as part of our standard care, no ethical approval was required and that the study was regarded as a quality improvement project.During the three periods, we included a total of 163 patients: for the pre-ADAPT, n = 55; for the ADAPT period, n = 50; and for the post-ADAPT, n = 59. Most of the patients were female (70%), and the mean age was 82 (range: 39 to 101) . During p = 0.10) and a TAD > 25 mm (p = 0.78). The main results of the study are depicted as scatter plots in p = 0.62). However, the median TAD was higher in the post-ADAPT period compared to the ADAPT period (p = 0.001)  .p = 0.15) and post-ADAPT period (5.1 (2–18) mm, p = 0.82).The ADAPT system did not significantly reduce the median protrusion of the lag screw of 5.7 (1–12) mm beyond the lateral cortex compared to the pre-ADAPT period (6.8 (2–15) mm, p = 0.21).There was no difference in the median fluoroscopy time when comparing the three periods (pre-ADAPT: 184 (62–786) seconds, ADAPT: 243 (112–532) seconds, post-ADAPT: 248 (86–506) seconds, p = 0.99) or post-ADAPT periods (p = 0.98).We did not find a reduction in the surgery time in the ADAPT period compared to either the pre-ADAPT . Similarly, there were no significant differences in the duration of surgery or fluoroscopy time (p = 0.21).In this prospective trial of the ADAPT system, we included patients with intertrochanteric fractures in three periods: a pre-ADAPT period, where patients were operated on with the standard Gamma3 intramedullary nail technique (n = 55); an ADAPT period, where patients were operated on with the use of the ADAPT system (n = 50); and a post-ADAPT period, where patients were operated on without the use of the ADAPT system (n = 59). The ADAPT system did not prevent outliers entirely. In fact, the number of outliers was still 11/50 = 22% when using the system. This reduction from 15/55 = 27% in the pre-ADAPT period was not statistically significant. The lateral protrusion of the lag screw was not significantly different between the three periods (p = 0.10) or for outliers with a TAD > 25 mm (p = 0.78). This is in line with the randomized controlled trial performed by Lilly et al. [We did not find a significant reduction in outliers when comparing the ADAPT period to the pre- and post-ADAPT periods for outliers with a TAD > 20 mm  but not when comparing the ADAPT period with the pre-ADAPT period (median TAD = 17) (p = 0.62). As the median TAD in all three periods was below 20 mm, this reduction in the TAD might be statistically significant, but it is not clinically relevant.We found a statistically significantly lower median TAD when comparing the ADAPT period (median TAD = 15.5 mm) with the post-ADAPT period (median TAD = 18.0)  pre-ADAPT, 6/50 (12%) ADAPT, and 8/59 (14%) post-ADAPT. Moreover, the ADAPT is designed to be an adjunct for all surgeons.A second limitation to our study is the lack of a power calculation. We did not perform a power calculation prior to this study, as we beforehand agreed that if the ADAPT system did not reduce the number of outliers significantly when used on 50 patients, we would discontinue its use in our department.Based on the data regarding outliers  provided in With a TAD > 20 mm, the combined pre-ADAPT and post-ADAPT rate of outliers was (11 + 4 + 15 + 8)/(55 + 59) = 38 outliers/114 patients = 33%, while the corresponding rate during the ADAPT-period was (8 + 3)/50 = 22%. Based on these findings, the post hoc power of the study  was only 28%. Consequently, a sample size calculation with a power of 0.8, an alpha of 0.05, and group incidences of 33% and 22% would require 257 patients in each group. In this light, the study can be argued to be underpowered.However, the advantage of the ADAPT was thought to be to reduce the outliers completely, i.e., a reduction from approximately a 25–27% rate of outliers (TAD > 20 mm) to 0%. In this case, only 42 patients would be needed in each group to have a power of 0.95 with an alpha of 0.05. The current study revealed that the ADAPT did not eliminate outliers completely. On the contrary, our study documents that outliers were still common despite the use of the ADAPT, i.e., 11/50 = 22%. Therefore, our initial hope and belief that computer-assisted surgery could entirely prevent or markedly reduce the number of outliers was not confirmed. Moreover, neither residents nor consultants liked to use the system . We therComputer-assisted fracture surgery is on the rise and has been extensively investigated in recent years ,20. AdeqIn the present study, TAD outliers (>20 mm) were still present in 11/50 = 22% of hip fracture patients being treated with the use of computer-assisted surgery (ADAPT for Gamma3 hip fracture nailing system). Based on these findings, the use of ADAPT was discontinued at our level 1 trauma center.