Semantic textual similarity (STS) is a fundamental natural language processing (NLP) task which can be widely used in many NLP applications such as Question Answer (QA), Information Retrieval (IR), etc. It is a typical regression problem, and almost all STS systems either use distributed representation or one-hot representation to model sentence pairs.In this paper, we proposed a novel framework based on a gated network to fuse distributed representation and one-hot representation of sentence pairs. Some current state-of-the-art distributed representation methods, including Convolutional Neural Network (CNN), Bi-directional Long Short Term Memory networks (Bi-LSTM) and Bidirectional Encoder Representations from Transformers (BERT), were used in our framework, and a system based on this framework was developed for a shared task regarding clinical STS organized by BioCreative/OHNLP in 2018.Compared with the systems only using distributed representation or one-hot representation, our method achieved much higher Pearson correlation. Among all distributed representations, BERT performed best. The highest Person correlation of our system was 0.8541, higher than the best official one of the BioCreative/OHNLP clinical STS shared task in 2018 (0.8328) by 0.0213.Distributed representation and one-hot representation are complementary to each other and can be fused by gated network. Electronic Health Records (EHRs) that record patients’ complete information, including family history, general situation, chief complaint, examination, lab test, diagnosis, assessment, and plan, etc., have been widely used to help medical experts to improve processes of care on patient outcomes. The key to secondary use of EHRs lies in high quality. However, the quality of EHRs has met challenges such as frequent use of copy-and-paste, templates, and smart phrases which lead to bloated or erroneous clinical notes . A studyAs many NLP applications such as QA, IR, etc. usually used STS as a core component, large quantities of researchers have contributed to STS and achieved great success. STS is a typical regression problem, and how to model sentence pairs is the key to solutions. There are two main types of representations to model sentence pairs: one-hot representation and distributed representation. The one-hot representation that depends on manually-crafted features suffers from sparsity. The distributed representation that learns dense real-value vector from unlabeled data automatically by neural networks have shown great potentialities. Most studies focus on one type of representations. In this paper, we proposed a novel framework to fuse the two types of representations using a gated network. In the case of distribution representations, we compared some current state-of-the-art neural networks such as CNN, Bi-LSTM, and BERT. To evaluate our method, we conducted experiments on the clinical STS corpus of BioCreative/OHNLP 2018 by comparing our method with the methods that only using one type of representation and the official best method on the clinical STS shared task. Experimental results showed that: 1) the proposed method achieved much higher Pearson correlation than the methods only using one type of representations. 2) BERT performed better than other distributed representations. 3) Our method achieved the highest Pearson correlation of 0.8541, higher than the best official one of the clinical STS shared task (0.8328) by 0.0213.There are two main types of sentence representation: (1) sparse one-hot representation based on manually extracted features. (2) densely distributed representation learnt from large labeled data. Within a long period, there have been a large number of feature extraction methods proposed to represent sentence by one-hot vector. Gomaa et al.  summarizsim, where s1 is a sentence of length m and s2 is a sentence of length n. We used sij to denote the j-th word of si. In this study, the similarity of a sentence pair ranged from 0 to 5, where 0 represents the two sentences are not semantically similar, and 5 represents the two sentences are semantically equal. Besides, we used D and O to describe a sentence’s distributed representation and one-hot representation respectively.Formally, the clinical STS task is to determine the similarity of a pair of given sentences, denoted by The BioCreative/OHNLP organizer manually annotated 750 sentence pairs with semantic similarity ranging from 0 to 5 for system development and 318 sentence pairs for system test. We further divided the 750 sentence pairs into a training set and a develop set using stratified sampling to guarantee that the develop set is a representative of the overall dataset. Figure http://www.nltk.org/) for tokenization and lemmatization; 2) converted Arabic numerals into English numbers. For example, the sentence “Indication, Site, and Additional Prescription Instructions: Apply 1 patch every 24 hours; leave on for up to 12 hours within a 24 hour period” became “indication site additional prescription instruction apply one patch every twenty four hour leave twelve hour within twenty four hour period” after preprocessing.We preprocessed each sentence as follows: 1) used NLTK tool  is obtained as follows:In this study, we investigated three types of distributed representations: Siamese CNN , Siameseavg _ pool is the average pooling operation, convolution is the convolution operation, s1 and s2 are the two input sentences.(2)Siamese RNN, similar to Siamese CNN, is composed of two RNNs that represent each one sentence respectively and share weights. In our study, we adopted Bi-directional Long Short Term Memory (Bi-LSTM) networks as an implementation of RNN, where each word i at s1 and s2 is represented as:where s1, s2) is described as:(3)BERT  is a language representation method to obtain deep bidirectional representations of sentences by jointly conditioning on both left and right context in all layers from free text unsupervised. In our study, the representation of a sentence pair  was denoted byThe sentence pair (https://github.com/google-research/bert).We trained a new BERT model on MIMIC III starting from the pre-trained model released by Google .Ngram(si)  is a N-gram set extracted from si. In our study, unigrams, bigrams and trigrams were considered.We followed Tian’s work  to extrad in eq. , and diss1, s2) R can be obtained in the following way:Inspired by the gated network mechanism in variants of RNN such as LSTM and GRU (Gated Recurrent Unit), we introduced a gate to leverage distributed representation and one-hot representation. Before fusion, we adopted the tanh function as an activation function to convert the two types of representation into the same space. So that the final representation of sentence pair , then concatenated the two types of representations, and finally fused the two types of representations with a gated network. All systems were evaluated on the clinical STS corpus of the BioCreative/OHNLP challenge in 2018, and Pearson correlation was used to measure the performance of the systems.As shown in Table In this study, we investigated three state-of-the-art distributed representation methods, that is, CNN, Bi-LSTM, and BERT, and proposed a novel framework based on a gated network to fuse distributed representation and one-hot representation of sentence pairs. Among the systems only using any one distributed representation or one-hot representation, the system using BERT achieved highest Pearson correlation, but the system using one-hot representation produced much higher Pearson correlation than the method using CNN or Bi-LSTM. Both concatenation and fusion of distributed representation and one-hot representation brought improvement, and the fusion with gated network performed better.N-gram overlapped by the two sentences, but a little semantically similar  when we applied the system using CNN or Bi-LSTM. The improvement because of concatenation or fusion of distributed representation and one-hot representation mainly came from sentence pairs of high similarity. As an illustration, we compared mean square error (MSE) on fractional similarity intervals as shown in Fig. The reason why the system using CNN or Bi-LSTM performed much worse than that using BERT or one-hot representation lies in the following two aspects: 1) the word embeddings used in CNN or Bi-LSTM were trained on a much smaller corpus than BERT; 2) one-hot representation had an advantage over CNN and Bi-LSTM on sentence pairs not very similar when the embeddings were trained on a small corpus. For example, it was easy to determine that “it be appropriate to retain the patient at the present level of care since the patient be make progress but have not yet achieve the goal articulate in the individualize treatment plan” and “the patient demonstrates the ability to fire the ta g and fhl of the operative extremity” are not semantically similar  when we applied the system using one-hot representation as there was no For further improvement, there are three possible directions as follows: 1) fuse multiple distributed representations with one-hot representation as different distributed representations may be complementary; 2) increase more data for word embedding training and model training; 3) introduce domain knowledge into our framework. All of them will be investigated in the future.In this paper, we proposed a novel framework to fuse distributed representation and one-hot representation using a gated network for clinical STS. Experiments on a benchmark dataset showed that the two types of representations were complementary and gated network was a good way for representation fusion.


Molecular chaperones assist proteins in achieving a functional structure and prevent them from misfolding into aggregates, including disease-associated deposits. The BRICHOS domain from familial dementia associated protein Bri2 (or ITM2B) probably chaperones its specific proprotein region with high β-sheet propensity during biosynthesis. Recently, Bri2 BRICHOS activity was found to extend to other amyloidogenic, fibril forming peptides, in particular, Alzheimer’s disease associated amyloid-β peptide, as well as to amorphous aggregate forming proteins. However, the biological functions of the central nervous system specific homologue Bri3 BRICHOS are still to be elucidated. Here we give a detailed characterisation of the recombinant human (rh) Bri3 BRICHOS domain and compare its structural and functional properties with rh Bri2 BRICHOS. The results show that rh Bri3 BRICHOS forms more and larger oligomers, somewhat more efficiently prevents non-fibrillar protein aggregation, and less efficiently reduces Aβ42 fibril formation compared to rh Bri2 BRICHOS. This suggests that Bri2 and Bri3 BRICHOS have overlapping molecular mechanisms and that their apparently different tissue expression and processing may result in different physiological functions. Molecular chaperones are part of this defence arsenal and can interfere with virtually all steps from co-translational protein folding to degradation, which promote the formation of correctly folded and functional proteins over-accumulation of self-assembled aggregates that may cause toxicity2.To maintain cellular homeostasis, organisms have evolved ways to prevent misfolded and aggregated proteins from causing cellular damage3. Many proteins can form amyloid-like fibrils in vitro5 but tissue deposits of specific proteins in the amyloid state are coupled to only about 40 diseases, including many severe neurodegenerative disorders6. Alzheimer’s disease (AD) is the most common cause of dementia, and there is no disease-modifying treatment available. AD is histopathologically characterised by the presence of extracellular amyloid plaques mainly in the neocortex and hippocampus, and these plaques contain fibrils of the amyloid β-peptide 1–40 (Aβ40 and 1–42 (Aβ42)7. AD is also defined by the formation of another type of protein deposit—intracellular neurofibrillary tangles composed of hyperphosphorylated tau protein8. The formation of Aβ and tau deposits is thought to result in the loss of synapse function, eventually leading to cell death and brain atrophy. The exact mechanisms, by which protein misfolding and aggregation result in neuronal loss and dysfunction in AD are unresolved, but it is believed that the main toxic agents are soluble oligomeric forms of Aβ rather than the mature fibrils10.Amyloid fibrils are the end-result of one type of misfolding and are composed of β-sheets in which the β-strands run perpendicular to the fibril axisBri2, chondromodulin-1 and prosurfactant protein C (proSP-C)11. The BRICHOS domain has been found in 10 protein families in humans, and BRICHOS containing proproteins share a common architecture12. These proproteins contain specific regions with high β-sheet propensity, which BRICHOS is believed to chaperone during biosynthesis15. Mutations in the BRICHOS domain of proSP-C result in lethal disease already in infancy, associated with lung amyloid composed of the proSP-C β-prone region, which supports the hypothesis that BRICHOS is a chaperone that prevents amyloid toxicity16. Bri2 is expressed in the CNS and in peripheral tissues. Mutations that extend its β-prone region result in amyloid deposits and familial British and Danish dementia18. Recombinant human (rh) BRICHOS domains from Bri2 and proSP-C reduce amyloid fibril formation and neurotoxicity of Aβ40 and Aβ4223, and transgenic overexpression of BRICHOS reduces Aβ42 related pathology in fruit flies24. These findings suggest that BRICHOS domains are able to prevent fibril formation and toxicity of other clients than the β-prone regions of their respective proprotein. In support of this, rh proSP-C BRICHOS prevents fibril formation of medin, a fragment of lactadherin that forms amyloid in the human aortic wall25, and we have recently found that Bri2 BRICHOS potently inhibits amyloid formation and toxicity of type 2 diabetes associated islet amyloid polypeptide (IAPP)26.The BRICHOS domain was initially defined by multiple amino acid sequence alignments of the proteins 14, and three residues are strictly conserved - two Cys and one Asp residue12.The conservation of amino acid sequences between BRICHOS domains from different proproteins is low, but their predicted secondary structures are similar27. However, Bri3 differs from Bri2 in several ways — it is exclusively expressed in the CNS, the C-terminal segment is cleaved by furin but the BRICHOS domain is apparently not released28, and it interacts with amyloid plaques and Aβ in different manners than Bri229.Bri3 is a 267-residue protein, and as other BRICHOS proteins, it contains an N-terminal part, a transmembrane segment, a linker region, the BRICHOS domain and a C-terminal segment. Bri3 is structurally similar to Bri2 with an overall 44% sequence identity30. Bri2 BRICHOS, however, has shown a more complex inhibition effect by blocking both a surface catalysed secondary nucleation and elongation of fibrils30.BRICHOS domains from different proproteins have been found to interfere with distinct steps in the reaction pathway from monomeric Aβ42 to fibrils. ProSP-C BRICHOS exclusively blocks the secondary nucleation step21. These observations raise the question of how different types of chaperone activities of BRICHOS are mediated. Isolated rh Bri2 BRICHOS monomers potently prevent hippocampal neuronal network toxicity of Aβ42, while dimers strongly suppress Aβ42 fibril formation. The dimers assemble into high-molecular-weight oligomers with an apparent two-fold symmetry, which are efficient inhibitors of non-fibrillar protein aggregation. Thus Bri2 BRICHOS affects qualitatively different aspects of protein misfolding and toxicity via different quaternary structures32. Rh Bri3 BRICHOS also reduces Aβ42 fibril formation but less efficiently than Bri2 BRICHOS29 but the detailed effects of Bri3 BRICHOS on Aβ42 fibril formation have not been studied. It is not known whether it similarly to Bri2 BRICHOS also prevents non-fibrillar protein aggregation, or whether it like proSP-C BRICHOS exclusively affects fibril formation.Moreover, Bri2 BRICHOS, but not the proSP-C BRICHOS domain also prevents non-fibrillar aggregation of partly denatured proteinsIn this study, we sought a more comprehensive understanding of Bri3 BRICHOS and its ability to reduce Aβ42 amyloid fibril formation and non-fibrillar aggregation.33 gave similar overall tertiary structures for Bri3 and Bri2 BRICHOS  Fig.  and nati31, but with somewhat increased residual molar ellipticity in the 205–225 nm regions. The CD spectra suggest that rh Bri3 BRICHOS is folded into a structure with a mixture of α-helices and β-sheet, which is compatible with the model structure  spectroscopy of rh Bri3 BRICHOS shows that its overall secondary structure content is similar to that of rh Bri2 BRICHOS Fig.  and to i35 was used. Incubation of rh Bri3 BRICHOS with bis-ANS shows a considerable increase in emission intensity and a marked blue shift in emission maximum to 472 nm, compared to bis-ANS in buffer; very similar to the behaviour of rh Bri2 BRICHOS ios Fig. . Rh Bri3ios Fig.  and no dios Fig. . Likewisios Fig. . Rh BRICios Fig. . There rios Fig. .Figure 321.In order to study potential complex formation between rh Bri3 BRICHOS domain and CS after thermal aggregation, samples were collected after completion of aggregation assay of a CS:BRICHOS mixture at 1:2 molar ratio, spun down and the supernatant as well as pellet fractions were analysed by SDS-PAGE and the supernatant was analysed by SEC. The results show that rh Bri3 BRICHOS forms a complex with thermo-destabilized CS that elutes in the void volume Fig. , which cThe rh Bri2 and Bri3 BRICHOS domains seem to preserve their folded states with only minor changes occurring at the elevated temperatures used in the aggregation assays, as judged from their CD spectra and native-PAGE  fluorescence. Rh Bri3 BRICHOS shows a dose-dependent reduction of Aβ42 fibril formation already at substoichiometric concentrations  for Aβ42 fibrillization are affected by rh Bri3 BRICHOS, global kinetic analysis was performed on the dataset for constant Aβ42 concentration and different rh Bri3 BRICHOS concentrations, leaving only one fitting rate, k2, k+, or kn, free  and regulate its processing and thereby have an effect on Aβ production31. The present study shows that also rh Bri3 BRICHOS has potent molecular chaperone activities. Bri3 BRICHOS forms mainly high molecular weight disulphide linked assemblies and only minor amounts of smaller species like dimers and monomers are observed  of the predicted models were: −1.37 for Bri2 BRICHOS and −1.42 for Bri3 BRICHOS. The I-Tasser database does not predict the formation of disulphide bonds. Therefore, we measured the distance between the sulphur groups of the two only cysteine residues and assumed that a disulphide bond is formed when the distance is below 2.3 Å. The measured distance between the sulphur groups of the Bri2 BRICHOS model was 2.019 Å, and that for the Bri3 BRICHOS model was 2.016 Å.Tertiary structure predictions of Bri2 BRICHOS (113–231) and Bri3 BRICHOS (112–230) were performed using the I-TASSER web serverThe amino acid sequences of Bri2 and Bri3 BRICHOS have been aligned with Geneious R7.1 using a Blosum62 score matrix.Escherichia coli Shuffle T7 cells; thrombin was used to release Trx-His- from S-tag-BRICHOS. Bacteria were cultured in Luria-Bertani (LB) medium with 100 μg/ml ampicillin at 30 °C, overnight (o/n) with constant stirring. Expression was induced at an OD600 = 0,6 − 0,8 by adding isopropylthiogalactoside (IPTG) to 0.4 mM and the bacteria were grown for another 4 h. Cells were harvested by centrifugation at 6000 × g for 15 min at 4 °C; pellets were suspended in 0.15 M NaCl, 20 mM sodium phosphate buffer (PB), pH 7.4 and stored at −20 °C.Gene sequences coding for the human, Bri3(112-230) and Bri2(90–236) were ligated to pET-32c(+) vector coding for thioredoxin (Trx), hexahistidine (His6), and S tags upstream of the cDNA insertion site. The Trx-His-S-tag-BRICHOS fusion proteins were expressed in et al.19 for Bri2 BRICHOS. Briefly, cells were lysed by sonication with Sonopuls HD2070 homogeniser  for 3 min  and centrifuged at 6000 × g for 20 min at 4 °C. Pellets were suspended in 2 M urea in 0.15 M NaCl, 20 mM PB, pH 7.4, and sonicated as described above for 5 min and centrifuged at 15557 × g for 30 min at 4 °C. The collected supernatant was filtered through a 5 μm filter and frozen at −20 °C o/n. Next day, the thawed supernatant was poured onto an IMAC Ni-Sepharose 6 Fast Flow column  pre-equilibrated with 2 M urea in 0.15 M NaCl, 20 mM PB, pH 7.4 and washed 3 times in series with 50 ml 0.15 M NaCl, 20 mM PB containing either 2 M and 1 M urea or 50 mM imidazole in final wash. The target fusion protein was then eluted with 300 mM imidazole 0.15 M NaCl, 20 mM PB, pH 7.4 and dialyzed against 20 mM PB, pH 7.4, while cleaving with thrombin (enzyme/substrate weight ratio of 0.002) for 16 h at 4 °C to remove the Trx and His6 tag. Molar extinction coefficients at 280 nm for measuring concentrations of for Bri3 and Bri2 fusion proteins were 31400 M−1 cm−1 and 25900 M−1cm−1 respectively.Purification of rh Bri3 and Bri2 BRICHOS was performed essentially as described by Peng −1cm−1 for rh Bri3 and 12045 M−1cm−1 for rh Bri2 BRICHOS. Final yields of rh Bri3 and Bri2 BRICHOS were 3–5 mg from 500 ml of bacterial culture, and the freshly purified samples were frozen at concentrations of 50–70 μM.After dialysis, the protein solution was reapplied to the Ni-Sepharose column and rh (S-tag) Bri3 BRICHOS were eluted with 20 mM PB, pH 7.4 and stored at −20 °C. Before the experiments, buffer exchange to 20 mM PB, 0.2 mM EDTA, pH 8.0 was carried out using PD-10 columns . Protein concentration at 280 nm was determined with a UV/Vis nanophotometer using a molar extinction coefficient 17545 ME. coli BL21 using ion exchange and size exclusion steps as described before47. For Aβ42 monomer isolation, crude proteins were lyophilized and then dissolved in 7 M GuHCl and run through Superdex 75 10/300 GL column  with 20 mM PB pH 8.0, 0.2 mM EDTA, 0.02% NaN3. The peptide concentration was determined by using an extinction coefficient of 1424 M−1cm−1 at A280-A300 nm. Purified monomers were aliquoted in protein low-binding tubes.Rh Met-Aβ1-42 (hereafter Aβ42) was expressed in For sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) under reducing conditions, SDS loading buffer together with dithiothreitol (DTT) was added to samples and heated at 95 °C for 5 min. For non-reducing SDS-PAGE, samples were mixed with SDS loading buffer lacking DTT and treated as above. Samples were separated on 4–20% gradient gels, visualised with Coomassie blue staining, and documented. For the native PAGE samples were mixed with native loading buffer, without DTT and SDS and separated on 10% gel.Circular Dichroism (CD) spectra for 10 µM Bri3 BRICHOS in 20 mM PB, 0.2 mM EDTA, pH 8.0 were recorded at 25 °C using Chirascan spectrometer (Applied Photophysics). Absorbance spectra from 260 to 180 nm with a wavelength increment of 1 nm were recorded in 1 mm path length quartz cuvettes. The bandwidth was set to 1 nm. Spectra shown are averages of 5 consecutive scans. As controls, rh Bri3 and rh Bri2 BRICHOS CD spectra were also recorded at 25 °C, after 24 h of incubation at 37 °C and after 2 h at 45 °C using a J-1500 CD spectrometer (JASCO) with a PTC-517 Peltier thermostat cell holder. CD spectra were recorded in 1 mm path length quartz cuvettes using wavelength from 260 to 175 nm with an increment of 0.5 nm. The bandwidth was set to 1 nm.Bis-ANS fluorescence emission spectra were recorded in quartz glass cuvettes using a Fluorolog- 3 spectrofluorometer . Fluorescence was excited at 395 nm and emission spectra recorded from 420 nm to 600 nm. The sample temperature was adjusted to 25 °C using a Peltier sample cooler. 1 µM rh Bri3 BRICHOS or rh Bri2 BRICHOS together with 2 µM bis-ANS were prepared in 20 mM phosphate buffer, 0.2 mM EDTA, pH 8 and measured after preincubation for 10 min at 25 °C.Dynamic light scattering (DLS) experiments were performed on a Zetasizer µV instrument  at 25 °C using the built-in standard values of the refractive index (1.330), viscosity (0.8872 cP) and material refractive index (1.45) for water. Protein samples were diluted in 20 mM phosphate buffer, 0.2 mM EDTA, pH 8 to a final concentration of 10 µM (Bri3 BRICHOS). The data represents the average of 15 measurements. Each measurement consists of 10 consecutive runs recorded for 10 seconds each.Rh Bri3 BRICHOS and rh Bri2 BRICHOS oligomers were isolated in 20 mM ammonium acetate pH 8.0 with a Superose 6 10/300 GL column. A narrow middle fraction of the broad main peak was collected and immediately stored on ice; the protein concentration was around 15 − 30 ng/μL. Samples of Aβ42 fibrils in the absence and presence of rh Bri3 BRICHOS were prepared after incubation of 5 µM Aβ42 monomers without or with 70% molar ratio of BRICHOS in 160 µl for 18 h. The samples were centrifuged at 22000 × g for 1 h at 4 °C. The pellet was resuspended in 20 µl 1x Tris-buffered saline. After sample preparation, 2 μL aliquot was adsorbed onto glow-discharged continuous carbon-coated copper grids  for 1 min. The grids were subsequently blotted with a filter paper, washed with two drops of Milli-Q water, and negatively stained with one drop of uranyl acetate [2% (w/v)] for 45 sec before final blotting and air-drying. The samples were imaged using a JEOL JEM2100F field emission gun transmission electron microscope  operating at 200 kV. Single micrographs of the sample were recorded on a Tietz 4k × 4k CCD camera, TVIPS  at magnification of 85,000 (pixel size 1.76) and 1.5–3 μm defocus was used and a total of 12 and 8 images were recorded for rh Bri2 and Bri3 BRICHOS, respectively.All rh Bri2 and Bri3 BRICHOS oligomer images were imported to EMAN2 (version 2.3) for further processing. After importing and estimating defocus with e2evalimage.py single particles in different orientations were selected from the images using e2boxer.py in manual mode, resulting in 2385 particles for rh Bri2 BRICHOS and 2394 particles for rh Bri3 BRICHOS. For each image, the contrast transfer function (CTF) parameters were estimated on boxed out regions containing particles (288 × 288 pixels for Bri2 and 240 × 240 pixels for Bri3) using the e2ctf.auto.py program. A reference-free 2D classification was performed afterwards. The Feret’s and minimal Feret’s diameters of 30 obtained 2D oligomer classes for each rh Bri2 and Bri3 BRICHOS were measured by bordering the oligomers and manual thresholding using Fiji ImageJ  software.48. After buffer exchange to 40 mM HEPES/KOH pH 7.5 by PD-10  chromatography CS was diluted to an end concentration of 600 nM. Rhodanese from bovine liver was purchased from Sigma , dissolved in PBS, pH 7.4 and concentration was determined by measuring the absorbance at 280 nm and using an extinction coefficient of 60640 M−1cm−1. The final concentration of 3 µM rhodanese was used in experiments.Thermal aggregation of citrate synthase (CS) from porcine heart  was monitored by following the light scattering at 360 nmThermal aggregation of substrate protein CS or rhodanese alone or in the presence of different concentrations rh Bri3 BRICHOS (determined with UV-Vis spectroscopy at 280 nm) was followed by measuring the change in the absorbance at 360 nm during 45 °C incubation for 2 h. Aggregation kinetics were measured in black, clear-bottom half-area polystyrene 96-well plates with non-binding surface  in triplicates and using FLUOStar Galaxy plate reader . Samples were prepared in triplicates and all measurements were repeated 3 times. The same procedure was followed for the rh Bri2 BRICHOS. Rh Bri3 BRICHOS and rh Bri2 BRICHOS protein concentrations were also quantified by BCA protein assay  and Bradford based assay (Bio-Rad Protein Assay) following the manufacturer instructions. Different dilutions of rh BRICHOS (stock concentrations determined by UV-Vis spectrophotometric measurement) were compared  of rh Bri3 BRICHOS species were measured in the same manner.Aggregation kinetics under quiescent conditions were studied by recording the ThT fluorescence intensity as a function of time in a FLUOStar Galaxy plate reader . The fluorescence was measured in black, clear-bottom half-area polystyrene 384-well microplates with non-binding surface , at 37 °C, using bottom optics with 440 nm excitation filter and 480 nm emission filter. For amyloid fibril formation kinetics of monomeric Aβ42 ThT analysis was carried out. Samples were prepared and quickly mixed on ice and pipetted into 384-well microplates in 4 replicates. Measurements were carried out in volume of 20 µl with each well containing 3 μM Aβ42 monomer, rh Bri3 BRICHOS or rh Bri2 BRICHOS at different concentrations relative to Aβ42, 10 μM ThT in 0.02% NaNrmax were extracted31. Second, the fibrillization kinetics was analysed by the nucleation model that is determined by primary (kn) and secondary nucleation (k2) events as well as for elongation (k+)36. Kinetic profiles at different Aβ42 monomer concentration were fitted globally, where the fitting parameters λ (for primary nucleation) and κ (for secondary nucleation) are dependent on nucleation rates by nC and n2 are the reaction orders for primary and secondary nucleation, respectively. In this model, the time dependence of the fibril mass M(t) is given by Eq.  were used for the determination of the hydrodynamic radius. Bri3 hydrodynamic diameter was derived from the Stokes radius obtained by comparison to a standard curve derived from elution volumes of standard proteins with known Stokes radii.Size-exclusion chromatography (SEC) was conducted using a Superose 6 10/300 GL column with ÄKTA pure 25 FPLC system . Rh Bri3 BRICHOS samples were run at a flow rate of 0.5 ml·min−1.For analyses of CS and rh Bri3 BRICHOS complex formation, 500 μL of each sample were eluted in 20 mM ammonium acetate buffer, pH 8.0 using flow rate of 0.7 ml·minSupplementary Information.


In traditional colorimetric lateral flow immunoassay (LFI) using gold nanoparticles (AuNPs) as a probe, additional optical transducers are required to quantify the signal intensity of the test line because it presents as a single red-colored line. In order to eliminate external equipment, the LFI signal should be quantifiable by the naked eye without the involvement of optical instruments. Given this objective, the single line test zone of conventional LFI was converted to several spots that formed herringbone patterns. When the sandwich immunoassay was performed on a newly developed semi-quantitative (SQ)-LFI system using AuNPs as an optical probe, the spots were colorized and the number of colored spots increased proportionally with the analyte concentration. By counting the number of colored spots, the analyte concentration can be easily estimated with the naked eye. To demonstrate the applicability of the SQ-LFI system in practical immunoanalysis, microalbumin, which is a diagnostic marker for renal failure, was analyzed using microalbumin-spiked artificial urine samples. Using the SQ-LFI system, the calibration results for artificial urine-based microalbumin were studied, ranging from 0 to 500 μg/mL, covering the required clinical detection range, and the limit of detection (LOD) value was calculated to be 15.5 μg/mL. Thus, the SQ-LFI system provides an avenue for the realization of an efficient quantification diagnostic device in resource-limited conditions. The development of an accurate and user-friendly diagnostic device is one of the most significant objectives in the clinical field. In the academic and industrial sectors, extensive research has proceeded to develop efficient diagnostic tools, such as point-of-care testing (POCT) biosensors ,4,5,6,7.However, despite the merits of LFI, traditional colorimetric AuNP-based LFI is still used in limited tests that only require simple negative or positive results, such as pregnancy and sexually transmitted disease tests, because of the drawbacks associated with signal evaluation ,17. TypiWith the aforementioned goal in mind, we developed a semi-quantitative LFI (SQ-LFI) method that does not require any external optical instrument to quantify the analytes A. For thTo validate the applicability of SQ-LFI, a practical immunoanalysis for renal failure was conducted using artificial human urine samples. As a model biomarker of renal failure, we selected microalbumin, which is measured in urine as a specific indicator of glomerular filtration malfunction ,26,27,28In this study, we demonstrated that our SQ-LFI system allows for instrument-free immunoanalysis that can be applied to practical diagnoses and efficiently manufactured at conventional facilities. A detailed description of the sensing system and its detection performance is provided in the following sections.4), trisodium citrate, Triton X-100, Tween-20, L-arginine, polyvinyl alcohol , glucose anhydrous, sucrose, albumin from human serum, and goat anti-mouse IgG antibody (capture antibody II) were purchased from Sigma-Aldrich . The Alexa Fluor® 555-labeled rabbit anti-mouse antibody was obtained from Invitrogen . Sodium chloride was purchased from Duchefa Biochemie . Bovine serum albumin (BSA) was obtained from BioWorld . Polyethylene glycol  was obtained from Polyscience . The mouse anti-human microalbumin antibody  and mouse anti-human microalbumin antibody  were purchased from Hytest . Artificial urine was purchased from Pickering Laboratories . For the reaction solutions, 50 mM PBS buffer (pH 7.2), 0.1 M PBS buffer (pH 7.2), PBSB buffer (PBS buffer and 1% BSA), running buffer , and double distilled and deionized water (DDW) were prepared.The NC membrane was obtained from mdi Membrane Technologies . Gold chloride hydrate . To prepare the test zone and control zone, capture antibodies I and II were dotted on the NC membrane using the conventional metal nibs of dip pens. Using the capture antibody solution as ink, antibody spots were dotted on the desired region of the NC membrane . The volThe SQ-LFI system comprises three procedures, as depicted in Even though the resulting SQ-LFI images can be evaluated by the naked eye, the thresholds of the strip images were adjusted using ImageJ software , Bethesda, MD, USA). The resulting adjusted images are provided in the manuscript, along with the original images to prevent arbitrary differences in the interpretation and acquisition of analytical results.In order to achieve a spot counting-based quantification strategy in LFIs, the effect of spot-pattern alterations on spot color development was examined, and the most efficient pattern was chosen. Using the previously described SQ-LFI strip fabrication method, three types of SQ-LFI strips with different test spot patterns were prepared. The patterns employed were as follows: a linear pattern comprising nine linearly arranged spots, a diagonal pattern comprising nine diagonally arranged spots, and a herringbone pattern comprising 15 herringbone arranged spots divided by three units. On the test zone spots of all strips, 1.0 mg/mL of capture antibody I solution was dotted. All control zone spots were prepared in the same pattern (three spots arranged in the transverse direction) with 1.0 mg/mL of capture antibody II solution. The SQ-LFI operating procedures were performed on the prepared strips with the microalbumin-spiked 0.1 M PBS sample containing 500 μg/mL of microalbumin.® 555-labeled rabbit anti-mouse antibody solution were dropped on the sample drop zone of the strip. Next, 80 μL of running buffer were applied to the sample drop zone to allow the fluorescence-labeled antibody solution to flow on the strip. The flow of fluorescent antibodies on the strip was observed using a fluorescence microscope. When the fluorescent antibody flow passed the capture antibody I spot on the strip, an image of the spot appearing on the fluorescence microscope was recorded and obtained.To demonstrate the split of the stream by the spot on the test zone, we observed the flow that passed the spots of the SQ-LFI strip. In this study, the fluorescence-labeled antibody was adopted as an optical probe instead of Ab-AuNPs because the fluorescence signal was much more intense than the color signal of the AuNPs. As a test zone on the SQ-LFI strip, nine spots were dotted linearly in the longitudinal direction with 1.0 mg/mL of capture antibody I solution. Then, 3 μL of 2 mg/mL Alexa FluorTo optimize the signal of the SQ-LFI strip, the effect of the concentration of the capture antibody solution applied to the test zone on spot color development was investigated. The test set consisted of five units of herringbone patterns . The test set was constructed with three different concentrations of capture antibody I solution. Test sets ①, ②, and ③ used 0.6, 0.8, and 1.0 mg/mL of capture antibody I solution, respectively. In each set, 0, 16, and 500 μg/mL of the microalbumin-spiked PBS sample were used to verify the optimum concentration of the capture antibody I solution for microalbumin analysis using the SQ-LFI.To demonstrate SQ-LFI performance in the quantitative analysis of a biomarker, various concentrations  of microalbumin-spiked PBS samples were analyzed. The test strip of set ① in the previous experiment, which comprised five units of herringbone patterns dotted with 0.6 mg/mL of capture antibody I solution, was used. To certify the reproducibility of the SQ-LFI, this calibration test was performed three times. In addition, the practical feasibility of the SQ-LFI for applications in the microalbuminuria test was verified using artificial urine samples and artificial diabetes urine samples with various concentrations of microalbumin . To certify the reproducibility of the SQ-LFI, this calibration test was performed five times. All of the resulting test strips were recorded as image files by a smartphone camera and reported with threshold-adjusted images to prevent arbitrary differences in the interpretation and acquisition of the analytical results. The obtained quantification results were registered in the microalbumin calibration curve.In traditional LFI, Ab-AuNPs are used as probes. These probes are captured on the test line of the LFI via sandwich-type immunoaffinity binding and are presented as a red-colored line. The captured probes are accumulated on the test line according to the concentration of the antigen in the sample. As a consequence, by analyzing the color intensity of the test line, the LFI can analyze not only the presence of the antigen but also quantify its concentration in the sample.However, since the intensity of the color on the strip is difficult to analyze without optical transducing instruments, the quantification of antigens with conventional LFI requires additional instruments. To overcome this drawback, we introduced the concept of a box-stacking animation to the newly developed SQ-LFI. This concept animation visualizes the charging status as several countable boxes to easily identify the charging status of an electronic device by the naked eye. By applying this concept, the test line of a conventional LFI, which presents an uncountable color intensity signal, was converted into test spots of in an SQ-LFI that comprised several countable colored spots. The concentration of the antigen is visualized by the appearance of colored spots and can be quantified by counting the number of spots with the naked eye. As the antigen concentration increases, the number of colored spots is increased in the SQ-LFI, unlike the color intensity increase in the test line of conventional LFI. In the opposite conditions, when the antigen concentration decreases, the number of colored spots is decreased in the SQ-LFI rather than the color intensity decrease in the test line in conventional LFI. Based on this principle, the antigen concentrations in the sample could be analyzed by counting the colored spots with the naked eye, and the analytical performance of the SQ-LFI was verified by analyzing various concentrations of the target analyte microalbumin.The immunoassay result of a conventional LFI is provided to the user as a single colored line. Because a line can be regarded as the sum of numerous dots, we divided the line into several spots and distributed them on the test zone of the strip. The distributed spots allow for the quantitative analysis of an LFI with the naked eye. However, the accumulated immunocomplexes on the spots could affect the flow on the strip because of their large components, such as antigens, antibodies, and AuNPs . The colA bundle of four images (①–④) is shown for each spot pattern test. The circled number ① indicates the spot pattern, ② suggests the prediction of flow, ③ shows the resulting image obtained by a smartphone camera, and ④ demonstrates the threshold-adjusted image to remove arbitrary interpretation. First, the pattern with nine linearly arranged spots A-① was t® 555–labeled anti-mouse antibody on the SQ-LFI strip is depicted in To support our interpretation, including our prediction of flow behavior on the LFI strip, the flow around the developed spots on the SQ-LFI strips was observed using fluorescence microscopy. The movement of the Alexa FluorThe three spots located on the front part of the strip, shown in Interestingly, although the spot arrangement pattern was similar to the linear pattern examined in the previous section, the fluorescent dye-based examination of spot development was different from the AuNP-based examination. In the AuNP-based examination of the linear-patterned strip, the flow was separated at the front end of the spot. In contrast, a distinguishable flow separation was observed after spot number iv in the fluorescent dye-based test. The difference between these two examinations originated from the presence of AuNPs, which are rigid and larger than biomolecules. Because the accumulated AuNPs physically blocked the flow due to their material properties, flow separation was more easily observed than in the fluorescent dye-based examination. Considering the fluorescent dye-based flow result and physical properties of AuNPs, specially designed signaling spots, such as the herringbone pattern, have the advantage when constructing AuNP-based SQ-LFIs.In the newly developed SQ-LFI technique, the color of the accumulated AuNPs in one test line was converted to several divided test spots. Therefore, for an accurate quantification assay using this principle, the factor of the divided spots was optimized. The major spot factors in the SQ-LFI were the number of spots and accumulation capacity of each spot. The number of spots was adjusted based on the target range of microalbumin (0 to 500 μg/mL) in this study. It was expected that the precise analysis of the desired range would not be possible with only 15 spots when used in the spot pattern test. Accordingly, 25 spots were applied to the test zone on the strip, which is the maximum number of spots that could be set on the strip with no interference from each other.After the number of spots was determined, the accumulation capacity of each spot was considered. In the test zone, the accumulation capacity of the microalbumin/Ab-AuNP complexes was mainly determined by the amount of capture antibody I spotted on the strip. The more antibodies per spot, the more complexes that accumulated on each spot. Thus, the concentration of the antibody used as ink increased, and it was expected that fewer colored spots would be observed when measuring the highest concentration of the target. To optimize this condition, we tested three different concentrations of capture antibody I solution with 500 μg/mL of the microalbumin sample.As shown in In the previous results, it was confirmed that the developed SQ-LFI could measure and distinguish the lowest and highest concentrations of microalbumin. To validate the feasibility of the developed SQ-LFI, a calibration study of microalbumin was performed prior to analysis of the real sample. For the calibration study, various concentrations of microalbumin-spiked PBS samples  were used. The optimized SQ-LFI strip, which comprised five units of herringbone patterns dotted with 0.6 mg/mL of the capture antibody I solution, was fabricated and used in the test. To verify the reproducibility of the developed system for the detection of microalbumin, the same experiment was repeated under the same conditions at least three times.The relationship between the concentration of microalbumin and the average number of colored spots is plotted as a calibration graph in Thus, the clinical range of microalbumin (from 30 μg/mL to 300 μg/mL) was covered. For further reliability, the original images and threshold-adjusted images are shown in Based on the reported results, it was verified that the developed SQ-LFI system could be used for the quantitative analysis of microalbumin under buffer conditions. However, in the development of a diagnostic system or device, the demonstration of its practical applicability in the analysis of real human samples is a very significant step. Therefore, to demonstrate the applicability of the developed system to human samples, an artificial urine solution containing various components  was prepared and used. In this solution, microalbumin was spiked with seven different concentrations , and these samples were analyzed with the developed SQ-LFI. The detection of microalbumin using the SQ-LFI was repeated under the same conditions at least five times to validate the reproducibility of the sensor.As shown in In addition, since many cases of renal failure are reported as a complication of diabetes, it is likely that there are patients with simultaneous renal failure and diabetes. Therefore, to include these patients, the developed SQ-LFI should have the ability to sense microalbumin even if the urine sample contains a high concentration of glucose. An artificial urine sample containing 500 μg/mL of glucose was prepared and used as a diabetes artificial urine sample. The result of the calibration curve is shown in As seen in this study, the coverage of the developed SQ-LFI covers the clinical range of microalbumin, and the degree of renal failure can be determined based on each cutoff value. In addition, samples with high concentrations of glucose resulted in the same calibration curves as those without glucose; thus, the same performance can be demonstrated for patients with renal failure regardless of whether or not they also have diabetes.We have developed an instrument-free SQ-LFI system with simple modifications to a conventional LFI strip. By converting the test line of the conventional LFI strip into bundles of spots arranged in a herringbone pattern, quantitative information on the target molecule can be provided as the number of colored spots on the test strip instead of color intensity. This approach allows for SQ immunoanalysis of the target antigen based on the counting of colored spots using the naked eye. Because SQ-LFI does not require any additional optical instruments, the developed immunosensing method can be used under conditions where electricity is not readily available. Furthermore, the analytical performance of SQ-LFI fulfills the clinical range requirements for renal failure, even in artificial urine and diabetes urine samples. Because the materials and fabrication procedures are the same as those used for conventional LFI, SQ-LFI can also be efficiently implemented using conventional facilities for LFI manufacturing.


Clostridium difficile infection (CDI) on nurses’ work in the hospital and the results were published elsewhere . Semi-structured interviews were conducted with 12 nurses. Saturation was characterized by the cumulative percentage of variability accounted for by PLS factors. After 12 interviews, this percentage was 51% which suggests that saturation was achieved at least on main themes. Two main themes identifying similarities in the experience of nurses caring for patients with CDI were identified: Organization/Coordination of the working day and Time-consuming work. Although dependent on the coding of qualitative data, PLS regression of quantitized data from qualitative interviews generated useful information for the determination of saturation.Saturation, a core concept in qualitative research, suggests when data collection might end. It is reached when no new relevant information emerges with additional interviews. The aim of this research was to explore whether a mixed methods design could contribute to the demonstration of saturation. Firstly, saturation was conceptualized mathematically using set theory. Secondly, a conversion mixed design was conducted: a set of codes derived from qualitative interviews were quantitized and analyzed using partial least squares (PLS) regression to document whether saturation was reached. A qualitative study conducted by other researchers prior to this work (i.e. none of the present authors was involved in this study) was used to test saturation using PLS regression. This illustrative qualitative study aimed to investigate the impact of  The determination of an adequate sample size to appropriately address a research question is a fundamental aspect of the data collection process in any context, qualitative or quantitative. In quantitative research, adequate sample size is determined using an inferential statistical framework, based on assumptions on type I and II error control. In qualitative research, the concept of saturation, also known as ‘data saturation’, has been proposed as the solution to determine an adequate sample size. Morse defined saturation as “data adequacy” which means that saturation is reached when data collected is sufficient to cover the themes of interest and that collecting further data will not bring new relevant information . SaturatMixed methods research (MMR) can be defined as “research in which the investigator collects and analyzes data, integrates the findings, and draws inferences using both qualitative and quantitative approaches or methods in a single study or program of inquiry”. MMR hasMMR offers a variety of study designs that are used depending on the research question. In the health outcomes field, one of the most common mixed methods designs is the convergent parallel design , 26. TheThe objective of this study was to explore whether a conversion mixed design using a quantitative approach could contribute to the determination of saturation in qualitative research, based on a new analysis of data from an existing qualitative study.Clostridium difficile infection (CDI) on nurses’ work in the hospital. Clostridium difficile is a common source of antibiotic-associated diarrhea and leads to nosocomial infection [Existing data from a qualitative study were used to address our objective. This qualitative study aimed to investigate the impact of the nfection . Semi-stnfection . The quanfection .We started by conceptualizing saturation in a quantitative framework. For this purpose, the focus was shifted from sample size to number of themes and set theory was used . It was The schematic illustration of the conversion mixed design used for our research question is displayed in The qualitative strand that was used in the Guillemin et al. (2015) study on which this one is based followed a standard process to address the question of saturation . Qualitai/ui score plot is the projection of the observations in the X-space (score ti) and in the Y-space (score ui) according to the PLS factor i. It shows how well the Y-space correlates with the X-space [In our study, existing qualitative data were quantitized to be used in the quantitative strand. Codes for each case were converted into numerical data with the help of the qualitative data analysis software program , 32. The X-space .For the purpose of investigating saturation with PLS regression, the interviews were split into two blocks of interviews, categorized sequentially: the first block is composed of a large part of the interviews conducted (i.e. the first 75% interviews) and the second block comprised the remaining interviews. The objective is to estimate the difference between the set of themes of interest regarding the research question (Π) and the set of relevant themes elicited during the interviews (Λ) by the difference between the first interviews and the last interviews . If the ▪j corresponds to the vector of the number of times each theme is coded in the j-th interviewX▪PLS is the vector of regression coefficientsB▪E is the matrix of residualsWhere:j+1-Xn) by the themes elicited in the set of the first interviews (X1-Xj). The PLS model was performed using SIMCA software (formerly SIMCA-P) [This model expresses the regression of the themes elicited in the set of last interviews (set of XSIMCA-P) .The final stage in the conversion mixed design, as in any parallel mixed methods design, is the meta-inference based on combining or comparing the results of the two strands: in this case, whether the results provided by the quantitative strand regarding saturation are supportive to those obtained from the qualitative strand.The authors of the qualitative analyses, which were reported earlier elsewhere, considered that saturation had been reached and that an understanding of how CDI affected nurses’ work was comprehensively captured at the end of the 12 nurse interviews (NIs) .PLS regression was performed to link the block of the themes elicited in the last three NIs to the block of the themes elicited in the first nine NIs. The PLS factors summarizing all the themes from the first nine NIs explained 51% of the variability of the themes from the last three NIs . Only thBoth quantitative and qualitative results suggested that saturation was reached in this illustrative qualitative study. PLS regression showed that saturation was reached for at least main themes while qualitative results suggested that saturation had been reached.PLS regression also allowed a more detailed exploration of the structure of the themes and the definition of profiles of the NIs, based on the first two PLS factors that captured most of the variability of the data. The association of the two blocks of NIs was observed using the correlation-loading plot of the two first PLS factors . The graThe interpretation of PLS regression requires the interpretation of what drives the creation of PLS factors: in our case, what are the themes that were contributing the most to the creation of these factors. This can be represented by the scatter plot of the projections of the themes in the space of PLS factors Figs  and 5. TThe objective of our study was to explore whether a conversion mixed design could contribute to the determination of saturation in qualitative research. In the illustrative qualitative study, results showed that saturation had been reached after 12 interviews . Our quaSince Morse pointed out that “there are no published guidelines or tests of adequacy for estimating the sample size required to reach saturation” , severalOur solution based on a mathematical conceptualization of saturation using test theory and quantitative multivariate analysis of quantitized data used frequencies  of the themes as input to quantitative analyses instead of binary occurrence (Yes/No). These frequencies were obtained through conversion using qualitative research software outputs to capture the frequency of occurrence of the theme while also providing information about how meaningful the theme was for the interviewee. This conversion of qualitative data into quantitized data does not come without assumptions: the frequency of a theme is seen as indicative of the importance of the theme for the interviewee but reduces the meaning of the theme into a fixed and single dimensional notion . We acknBesides of the type of data used, other factors influence when the saturation has been reached. These include the research question which is of extreme importance, the interviewee characteristics, the relevant information obtained from each interviewee, the sampling strategy, the qualitative method used and how the data have been analyzed qualitatively . In partOur conceptualization of saturation requires different sets of information. For its operationalization, these sets need to be estimated. For this purpose, we split the data from the interviews into two blocks: the first three quarters of the interviews (i.e. the first nine NIs) constituted the first block and was presumed to represent the knowledge established by the research; the second block (i.e. the last three NIs) was constituted of the remaining quarter of the interviews and potentially represented new information. This split was done using the chronological order of interviews because the common sampling and analytical approach in qualitative research allows for emergence of new themes and the possibility that the coding may change over time, building on the experience of the qualitative researcher. This therefore meant that the most stringent test possible regarding the potential for differences in themes for the two groups was applied. Also, it was decided to use a group of interviews to characterize the new information and not a single interview (i.e. the very last one) because a single interview might be a complete outlier. Other specifications of our proposed approach are possible (e.g. different splits into interview blocks through an iterative process) and should be explored to determine the most appropriate way to provide supportive evidence on saturation.For the quantitative strand of our MMR, PLS regression allowed our conceptualization of saturation to be operationalized, but it also provided useful additional information on the qualitative data by identifying interviewee profiles based on the themes they expressed. PLS regression features provided a detailed typology of NIs and the pattern of themes for both first and last NIs. For example, the various PLS outputs indicate that the two NIs from Group 1 (NI8 and NI9) and one nurse from Group 2 (NI10) were similar, despite being in different groups, because each expressed the theme n°58 (caring for patients with CDI affected the organization of their working day) as something critical to them during their interview.We focused on qualitative studies using individual interviews for data collection and thematic analysis for analytical methodologies . These aFinally, our research provides an application of MMR in the health outcomes field. We demonstrated how a conversion mixed design can provide additional insight on saturation in qualitative research. This expands the toolbox of MMR solutions to address health outcomes research questions. This example, in which a quantitative technique helps inform a typical qualitative question, also shows that qualitative and quantitative researchers can benefit from working closely together and comparing their perspectives. Doing so can lead to innovative solutions for the questions they routinely face in their research.Our proposed conversion mixed design, applying PLS regression to data collected in a qualitative study, operationalizes a formal mathematical conceptualization of the core concept of saturation in qualitative research and allows additional supportive, quantitative evidence on saturation to be generated. In our case study, not only did our MMR approach strengthen the demonstration of saturation, it also provided useful substantial information on the research question. Hence, this application of conversion mixed design opens interesting perspectives for the exploration of data generated by qualitative research in the health outcomes field.S1 TableNI = Nurse interview; Cdiff = Clostridium difficile infection.(XLSX)Click here for additional data file.S1 Appendix(DOCX)Click here for additional data file.


Simple tools are applied to chromatographic resolution and detection of known and novel diphosphoinositol phosphates without resort to radiolabeling approaches. It is shown that inositol tris/tetrakisphosphate kinase 1 and inositol pentakisphosphate 2-kinase comprise a reversible metabolic cassette converting InsP4 into 5-InsP7 and back in a nucleotide-dependent manner. Thus, inositol tris/tetrakisphosphate kinase 1 is a nexus of bioenergetics status and inositol polyphosphate/diphosphoinositol phosphate metabolism. As such, it commands a role in plants that evolution has assigned to a different class of enzyme in mammalian cells. The findings and the methods described will enable a full appraisal of the role of diphosphoinositol phosphates in plants and particularly the relative contribution of reversible inositol phosphate hydroxykinase and inositol phosphate phosphokinase activities to plant physiology.Inositol polyphosphates are ubiquitous molecular signals in metazoans, as are their pyrophosphorylated derivatives that bear a so-called ‘high-energy’ phosphoanhydride bond. A structural rationale is provided for the ability of Arabidopsis inositol tris/tetrakisphosphate kinase 1 to discriminate between symmetric and enantiomeric substrates in the production of diverse symmetric and asymmetric  Myo-inositol hexakisphosphate (InsP6) is the predominant form of phosphorus storage molecule in plants, where in storage organs and tissues it may accumulate to several percent of dry weight ), unlike its metabolic neighbors, InsP4 and InsP6 [5 [2-OH] and InsP5 [1/3-OH] P4 and InsP4] P4, but that the axial 2-OH is inappropriately oriented for phosphorylation. Were it to adopt the pose of InsP6, we would expect to see a 5-PP-InsP4 product P5 (InsP5 -OH), unl[1/3-OH] . The lac,5,6)P4] . We suggown in 6 . The lac5 is, however, not the only InsP5 present in plants, multiple peaks of InsP5 have been detected by radiolabeling ) yielded a novel product that is not InsP6 P4 P5, nor any of the other InsP5 isomers, are phosphorylated on the vacant hydroxyl  occupy new sites which we name D′ and F′, respectively. Subsite D′ involves residues Asp63, Asp150 and His156, whilst F′ involves His156 and Ser225. These predicted subsites presumably play a role in helping to ameliorate the problems arising from the need to accommodate the steric bulk and phosphate crowding of these substrates.The two ligands adopt similar poses in their predicted low energy complexes: binding modes quite dissimilar to those seen for InsPr et al. . However4s for which there are 30 theoretical possibilities, five for each InsP5 ‘parent’, does not allow facile identification of the novel ITPK1 product on chromatographic grounds. The near micromole quantities required for NMR analysis preclude easy confirmation of identity.The commercial unavailability of PP-InsPs, especially PP-InsP4 1-hydroxykinase activity for ITPK1 affords explanation of itpk1 phenotype P4 InsP4, despite synthesis of [32P]ATP and an increase in ATP peak area (in the UV254 channel). Significantly, the reaction did not generate orthophosphate product P5 1-phosphotranferase to ADP (ATP synthase) activity, i.e. the phosphorylation of the preferred enantiomeric (asymmetric) substrate to meso- (symmetric) product is reversible in generating the same enantiomer of InsP4. Using this more common HPLC method we were also able to compare the efficiency of phosphorylation of InsP4, InsP5 and InsP6 substrates P5 a slightly weaker substrate than InsP6. In 4 product of phosphorylation of InsP5 elutes between InsP5 (InsP5 [1-OH]) and InsP6 on Partisphere SAX HPLC.By labeling of kinase reaction products with [γ-32P] see  and use ectively . Again,  product . These dbstrates . InsP4 is responsive to nucleotide ratio, which taking account of AMP is encapsulated as a metabolic concept in the term energy charge [6 kinase for ATP [7. Similarly, the Km ATP of Arabidopsis ITPK1 (1.2 mM) poises the activity of this enzyme within the estimated physiological range of this nucleotide in the cytosol of plants [4 and InsP5, InsP6 and 5-InsP7, and for that matter InsP5 and the presumed 5PP-InsP4, are responsive to energy status. Here, by defining the reversibility of ITPK1 we show that the extent and direction of flux between InsP4 and 5-InsP7 is responsive to nucleotide ratio  in the manner of IP6K and Kcs1 [AtITPK1 (this study) is not resolved. Clearly, the example of AtITPK1 illustrates how reversibility of the activity(s) of full-length VIH1/2 is critical to our understanding of phosphate homeostasis, since between them ITPK1 and VIH1/2 set the balance between 5-InsP7 and 1,5-InsP8 as ligands of SPX-domain-containing proteins.The plant orthologs of PPIP5K have proved recalcitrant to study as full-length enzymes, but plants bearing deletion of Vih1 and Vih2 show constitutive Pi starvation responses recapitulating itpk1 phenotype ,15. The and Kcs1 ,41,49 anReversibility of plant inositol phosphate (hydroxyl) kinases is, however, well documented for ITPKs ,65 and IAtITPK1's contribution to InsP and PP-InsP metabolism, Saiardi and co-workers [3 via InsP5 to InsP5 that is paralleled in duckweed [7 and InsP8 in duckweed [8 synthesis therein is catalyzed through the contribution of orthologs of AtITPK1 and AtIPK1 whose reversible nature in 5-InsP7 synthesis/turnover is revealed here P4 and InsP6 [6 is typically two orders of magnitude more strongly labeled, but not in vegetative duckweed [itpk1 mutants, viz. increase in InsP4 and decrease in 5-InsP7.Moreover, our analysis suggests that ITPK1's substantially greater activity for InsPnd InsP6 . Indeed,duckweed ,36. Whil6/5-InsP7 phosphotransferase activity, to wholly different enzymes in plants and mammals. ITPK1, and perhaps ITPK2, assume the role of IP6K, or vice-versa, despite the presence of ITPK1 homolog in mammals. This places special emphasis on ITPK1. As we have shown, itpk1 mutants make less InsP6, InsP7 and, most likely, InsP8, and hyperaccumulate phosphate [8 as the cognate binding partner for SPX1 which interacts with the master transcriptional regulator, PHR1, of phosphate starvation responses. Consistent with studies in barley leaves [7. This is consistent with the nucleotide ratio-dependent control of ITPK1 that we demonstrate here. Others, however, have reported that whole seedlings starved of phosphate, and hence showing full phosphate starvation responses, increase nucleotides and ATP/ADP ratio approximately 2-fold on re-supply of phosphate [Most interestingly, perhaps, our work reveals how evolution has assigned the same function, an eminently reversible and nucleotide-sensitive InsPhosphate . Others hosphate ,16 have y leaves , we havehosphate .6 kinase activity [Of course, plants are photosynthetic autotrophs, which yeast and mammals are not. Plants couple phosphate import across the chloroplast membrane to export of triose phosphate for growth, in an obligatory manner. These points caution that there are substantive differences in phosphate homeostasis between eukaryotes, extending to the engagement of multiple SPX-domain proteins in plants . Just asactivity ,13 does activity . If planactivity  could be


Dear Editor,in situ after surgery, which can minimize patient complications and pain.In this video (Video S1 in the online Supporting Information), we propose a modified natural orifice specimen extraction surgery (NOSES) technology, called three‐trocar tubeless NOSES, to radically resect rectosigmoid cancer; this procedure can avoid a large abdominal incision for extraction of the specimen. Only three trocar incisions are used to complete the whole procedure, and no tubes  are left Our patient was a 62‐year‐old man with a high rectal lesion shown on colonoscopy and pathologically confirmed as adenocarcinoma. The CT scan showed this to be localized in the upper rectum without distant metastasis.We confirmed there was no liver or omental metastasis. Next, we dissected the lymph nodes and soft tissue along the inferior mesenteric artery. Meanwhile, we expanded the plane to free the sigmoid colon in order to stretch the colon easily later. After skeletonization of the distal rectum, we closed the rectal lumen at the distal margin by ligation. After an iodophors wash, we closed the proximal lumen by ligation and cut the bowel using a Harmonic Scalpel. A stapler anvil was placed into the abdominal cavity after separation of the bowel wall. Then, the specimen was amputated from the proximal colon and extracted from the anus. The distal lumen was closed using an Ethicon Endo GIA. Subsequently, we placed the stapler anvil into the proximal lumen and completed the anastomosis, and no leaks were found. The whole procedure was completed after closing the mesocolon and the trocar incisions.The authors declare that they have no conflict of interest.This study was supported by the National Basic Research Program of China (973 Program) , the National Natural Science Foundation of China , the Natural Science Fund for Distinguished Young Scholars of Guangdong Province , the Tip‐top Scientific and Technical Innovative Youth Talents of Guangdong special support program , Project 5010 of Clinical Medical Research of Sun Yat‐sen University‐5010 Cultivation Foundation , the Natural Science Foundation of Guangdong Province , the Program of Introducing Talents of Discipline to Universities, and National Key Clinical Discipline (2012).Video S1. Three‐trocar tubeless natural orifice specimen extraction surgery in rectosigmoid cancer – a video vignette.Click here for additional data file.Data S1. Script of the video.Click here for additional data file.


Malnutrition has become a prevalent condition, with European and international studies reporting rates of approximately 25–40% in hospitals. We set out to perform a multi-center cross-sectional study to assess malnutrition rates in Slovenian hospitals and to convert the findings into a mobile application suitable for use by nurses and staff at the bedside. In addition, we examined the association of the results of this mobile application with parameters for body composition measured by bioimpedance method, muscle strength, anthropometrics, and specific blood markers.We selected the Nutritional Risk Screening 2002 (NRS-2002) method, the second version of the modified short-form of Mini-Nutritional Assessment (MNA-SF), and the diagnostic criteria for cachexia proposed by Evans (CDE) as evidence-based methods for estimating the risk of and prevalence of malnutrition or/and cachexia. The methods were converted into the Android mobile application named MalNut that was used in three Slovenian hospitals by nurses and dietitians.We applied NRS-2002 and MNA-SF to screen for malnutrition risk and to assess malnutrition in 207 individuals aged 18 years and older, regardless of gender or reason for hospitalization during 1-week periods. Totally, 98% of these patients consider nutrition an important part of medical treatment care. NRS-2002 estimated the malnutrition risk to be 66.3%, which includes both patients to be at risk for malnutrition and patients that are truly malnourished. The malnutrition risk in the elderly (65+) estimated by MNA-SF was 39.6% and malnutrition 42.5%. When applying the CDE score in these two categories, 66.7% were identified as cachectic and 21.4% as pre-cachectic. In the patients assessed with the CDE score, malnutrition risk increased with higher extracellular water and decreased body mass index, hemoglobin, phase angle, and muscle strength. In all, 75% of patients assessed as high risk for malnutrition by NRS-2002, were identified as cachectic and 15.7% as pre-cachectic. In NRS-2002 assessed patients, this risk increased with higher C-reactive protein and lower phase angle.The study showed that both malnutrition and cachexia are largely overlapping notions and are common in hospitalized adults in Slovenia. The MNA-SF and NRS-2002 tools showed that malnutrition risk was not significantly correlated with age, gender, serum albumin, but was correlated with lower phase angle, CRP, and muscle strength in elderly patients. The results have been used to develop further nutritional interventions in Slovenia. Malnutrition is common worldwide phenomenon and represents a major medical and economical issue, also in developed countries. However, it is difficult to assess the magnitude of the problem as malnutrition represents a wide variety of ailments like exclusive lack of sufficient food intake, leading to starvation related loss of fat mass and fat-free mass, and inflammation related sarcopenia and cachexia in inflammatory conditions, like disease, trauma, cancer, and ageing. All these conditions are frequently encountered in daily practice –4. As diMalnutrition means poor nutrition and encompasses both undernutrition and overnutrition. In the case of chronic disease and its impact on dietary intake and nutritional status, the term malnutrition generally describes “a disordered state of nutrition, caused by a varying combination of a negative (or positive) nutrient balance and inflammation, leading to abnormal body composition and function , 6, 7. IThe prevalence of malnutrition is high. European studies and studies outside Europe report rates of approximately 25–40% in hospitals, 20–25% in nursing homes, and 15–20% at home . When nuOptimizing nutritional intake is simple and relatively inexpensive, especially when detected early. Yet, many chronically ill and older patients are at risk to eat insufficient amounts of high-quality food due to the low priority given to ensuring adequate nutritional care for all patients, whether living at home, in the hospital or in long-term care centers. However, the inflammatory activity induced by chronic disease and to some degree also by the ageing process itself is difficult to counter. This inevitably leads to gradual muscle loss. However, adequate nutrition remains important, to counter additional ill-effects of inadequate nutritional intake.Cachexia is a very similar notion as malnutrition and is a multifactorial and complex metabolic syndrome associated with underlying illness and defined by an ongoing loss of skeletal muscle with or without concomitant loss of fat, which cannot be fully reversed by conventional nutritional support and leads to progressive functional impairment . Its patSeveral chronic diseases, such as cardiovascular disease, cancer, and chronic respiratory diseases (COPD), are conditions that contribute to cachexia. Cachexia prevalence in these disease states amounts to 28–57% in cancer, 16–42% in chronic heart failure, and 27–35% in COPD . MoreoveIn Slovenia, the national nutritional recommendations for malnutrition screening were published in 2008 . The SloThe purpose of the Slovenian multi-center and cross-sectional study presented in this paper was to utilize evidence-based methods to estimate the prevalence of malnutrition and cachexia in hospitalized adult patients. The additional objective was to examine the association between demographic, anthropometric, certain biochemical, and body composition parameters with impaired nutritional status assessed with the mobile bedside application. The secondary aim was to validate the method and use the data obtained as a platform to develop further nutritional interventions.Nutritional Risk Screening 2002 (NRS-2002): NRS-2002 is a tool for nutritional risk screening based on the analysis of 128 trials. It is based on the concept that nutritional support is required in patients who are severely ill with increased nutritional requirements, or who are severely undernourished, or who have certain degrees of severity of disease in combination with certain degrees of undernutrition [utrition . This toThe Mini-Nutritional Assessment (MNA): The MNA is a screening tool developed for detecting the presence of malnutrition risk in the elderly. Originally developed as a 30-point measurement, the MNA has been modified into a short form (MNA-SF) to provide a more practical tool while preserving the accuracy of the original. The classical MNA-SF comprises six questions addressing food intake and appetite, weight loss, mobility, acute illness or stress, dementia or depression, and BMI. The classical MNA-SF offers a rapid tool for excluding well-nourished older people, but does not differentiate between the nutritionally at risk and the malnourished individuals as in the original MNA. Therefore, we used the new MNA-SF which enables the replacement of BMI with calf circumference when BMI is not available and can clearly differentiate among the three categories of well-nourished, at risk for malnutrition, and malnourished patients. The measurement is easy to implement in clinical settings and takes less than 4 min to complete. In 2009, the MNA-SF was revalidated in a receiver operating characteristics analysis of 12 databases involving 2032 study participants from around the world [he world . ResultsCachexia diagnosis proposed by Evans (CDE): This diagnosis is based upon a definition that cachexia results from the adaptation to an underlying illness such as cancer [s cancer . The ills cancer , showings cancer  with thes cancer .We selected the following evidence-based methods for estimating the prevalence of the risk malnutrition by two standard scoring tools and according to the consensus definition of cachexia see Fig. :NutritioThe evidence-based methods NRS-2002, MNA, MNA-SF, and CDE were converted into a mobile application  that can be used across all health and care settings by nurses and dietitans . The appIn addition to the nutritional and screening tools, we added a general question about the patient’s awareness of the importance of nutritional treatment during the illness.This multi-center and cross-sectional study utilized NRS-2002, MNA, MNA-SF, and CDE tools to screen and assess all newly admitted patients hospitalized at the following Slovenian hospitals: the Oncology Institute Ljubljana (OI), the Gastroenterology Clinic of the Medical Center Ljubljana (GC), and the Peter Držaj (PD) Hospital Ljubljana. Screening and assessment were conducted for the risk of malnutrition and cachexia.The algorithm design is presented in Fig. 2).For MNA-SF, a total score of ≤7 indicated malnutrition and a total score of 8–11 a risk for malnutrition, while for NRS-2002 a total score of ≥3 indicated an increased risk for malnutrition, also including malnutrition. For CDE, the malnourished patients were diagnosed with cachexia if they were facing at least three out of five health problems  and losing at least 5% of weight in 12 months or less  study.The study group consisted of a convenience sample of 207 individuals aged 18 and older, regardless of gender or reason for hospitalization, admitted to the OI, GC, and PD hospitals during 1-week periods from June to September 2012. In OI, GC, and PD, respectively 150, 42, and 15 subjects admitted to all inpatient departments were included.All adult patients newly admitted to the hospitals were eligible for participation in the present study. Excluded individuals were those who expired prior to undergoing the nutrition screen, and a few patients, who were too weak to participate. All study participants signed a written consent form. During the study no patient withdrew the consent. Before signing the informed consent, we asked patients “what they think about nutrition” in order to assess their awareness of the importance of nutrition care during illness and disease treatment.Demographic characteristics, including participant age, gender, and community health center were extracted either from the patient’s medical record or elicited from the patient if not recorded in the medical record. Blood values determined on admission, including hemoglobin concentration (Hb), C-reactive protein (CRP), and serum albumin (SA), were extracted from the patient record. Both demographics and blood values were entered into the mobile application MalNut to be considered in the screening procedure.The study participants were weighed on a hospital scale in the room in which they were hospitalized. For patients, who could not stand for weighing, weight was self-reported. The patient himself/herself reported the height. Self-reported weight and height have been reported to be acceptable substitutes for directly measured weight and height when using the NRS-2002 .2) using either directly measured or estimated values for weight and height.To reduce variability, weight and height were performed by well-trained dietitians who were in charge of data acquisition. The data were entered into the mobile application MalNut, which automatically calculated BMI as weight (kg)/height , while muscle strength was measured by a hand dynamometer. Both measurements were performed by well-trained dietitians in the rooms in which the study participants were hospitalized, and stored in MalNut. Patients were in the supine position while body composition was measured. Muscle strength was measured in the upright position, as recommended. In few bedridden patients, it was measured in the lying position.Bioelectrical impedance was measured by the BodyStat’s QuadScan 4000 using several frequencies . At these frequencies, BIA was able to predict body fat, lean body mass, total body water, fat-free body mass (FFM), extracellular water (ECW), intracellular water, body fat mass index, FFM index, and phase angle (PA).The patient’s muscle strength was measured by the Baseline hydraulic hand dynamometer 12-0240.All documentation relating to the survey has been open to inspection.A convenience sample of 207 individuals hospitalized at the OI (150 patients), GC (42 patients), and PD (15 patients) participated in the study during the data acquisition period. In the study design, a sample size of 600 individuals was anticipated, which would provide a confidence level of 95% and a 4% margin of error to estimate the prevalence of malnutrition. Because of the study time constraint, only 207 subjects were sampled during the data acquisition period. This sample size provided a prevalence estimate confidence level of 95% and a 7% margin of error.http://opkp.si) for data storage and analysis. The analysis results provided by OPEN were imported into SPSS v. 21.0 , which was used for statistical analysis.Data were recorded by the mobile application MalNut that is connected to the Open Platform for Clinical Nutrition  that is more appropriate for small sample sizes (<50 samples), but can also handle sample sizes as large as 2000. If the Sig. value of the Shapiro–Wilk test was greater than 0.05, the data were treated as normal.Distributions of continuous variables were assessed for normality using the Shapiro–Wilk test (cutoff n (%), respectively. Continuous variables were compared with high malnutrition risk using the unrelated t test or the Mann–Whitney U test for independent measures.The proportion of malnourished individuals was estimated by dividing the number of malnourished individuals by the total number of the surveyed patients. Continuous and categorical variables were described using mean ± standard deviation and by frequency counts expressed as P < 0.05.Associations between continuous variables were described by calculating Pearson’s or Spearman’s correlation coefficient as appropriate, while associations between categorical variables were assessed using the chi-square test. All the tests were two-sided and considered as significant at A total of 207 adults  participated in the study. This represented 73% of all individuals admitted to the participating hospitals during the data acquisition period.Totally, 98% of patients considered nutritional care to be an important treatment measure.The NRS-2002 was utilized for 101 adult study participants of age less than 65 years. Altogether, 67 patients (66.3%) were identified as at risk for malnutrition . The response patterns to the NRS-2002 is shown by malnutrition risk status in Table The MNA-SF was utilized for 106 adult study participants of age 65 years and older. Among these participants, 42 patients (39.6%) were identified as malnourished  and 45 (42.5%) at risk of malnutrition. This reflects impaired nutritional status in 76.1% of elderly. The response patterns to the MNA-SF is shown by malnutrition risk status in Table t(59) = 2.9, P < 0.01, and lower PA ((4.8 ± 1.4 vs. 5.7 ± 1.0), t(98) = −3.3, P < 0.01). Both CRP and PA were weakly correlated with total NRS scores. While the correlation between CRP and total NRS scores was positive but statistically insignificant (rho (101) = 0.2, P = 0.08), the correlation between the PA and total NRS scores was negative and statistically significant (rho (101) = −0.3, P < 0.01).The NRS-2002 and MNA-SF populations are listed according to nutritional status in Table P = 0.00), significantly lower K-Hb , significantly higher ECW , significantly lower PA , and significantly lower muscle strength . The correlation between BMI and total MNA-SF scores was positive and statistically significant (rho(106) = 0.5, P = 0.00). Also the correlation between K-Hb and total MNA-SF scores was positive and statistically significant (rho(106) = 0.2, P = 0.03), while the correlation between ECW and total MNA-SF scores was negative and statistically significant (rho(106) = −0.3, P = 0.01). The correlation between PA and total MNA-SF scores was positive and statistically significant (rho(106) = 0.4, P = 0.00), as well as the correlation between muscle strength and total MNA-SF scores (rho(106) = 0.3, P < 0.01).In MNA-SF assessed patients, malnourished subjects had significantly lower BMI  participants answered that they do not believe in the importance of nutritional care, we can conclude that awareness among patients is high, supporting activities to improve nutritional state that is often prevailing in health care.As there is no international consensus on a single “best” nutrition screening and assessment tool, we applied the MNA-SF and NRS-2002 tools to screen and assess older patients (aged 65+) and other adults, respectively. While the malnutrition risk in the elderly estimated by MNA-SF was 39.6%, the NRS-2002 estimated the malnutrition risk to be 66.3%. However, as NRS 2002 screens risk for malnutrition, part of these patients is malnourished already. Both tools showed that malnutrition risk was unrelated to age, gender, SA, and most BIA parameters. In MNA-SF assessed patients, the malnutrition risk increased with higher ECW and lower BMI, Hb, PA, and muscle strength. In NRS-2002 assessed patients, this risk increased with higher CRP and lower PA. Our results for MNA-SF assessing the older patients are consistent with reports from other hospitalized populations in Switzerland, China, Italy, and Israel . HoweverP < 0.01), while the correlation between cachexia and SA was not statistically significant. SA was measured in a selected group (65.1%) of participants.Among MNA-SF patients assessed as malnourished, 66.7% patients were identified as cachectic. Among NRS-2002 patients assessed as high risk for malnutrition, 76.0% patients were identified as cachectic. Patients with cachexia usually have a low SA and CRP values slightly above normal. Increasing levels of CRP provide a rough measure of chronic inflammation. In a weight-losing patient with a normal SA and a normal or slightly elevated CRP, the physician should be particularly alert for alternate causes for weight loss. Our survey showed for both MNA-SF and NRS-2002 assessed patients, there was a statistically significant correlation between cachexia and CRP (Our data also indicate that body composition measurement with bioimpedance is a useful clinical tool. We confirmed the value of PA as an additional clinical marker for nutritional risk detection, what was already shown by ref. .Results also reflect differences in malnutrition and cachexia prevalence among hospitals. Despite the IO being a specialized cancer hospital, the prevalence of both nutritional disorders is lower, possibly because this hospital has established a clinical nutrition unit Fig. .Malnutrition and cachexia are prevalent nutritional disorders in selected Slovenian hospitals. As it represents an important medical problem for patients and the health system, there is an urgent need to address the problem more systematically. The data presented here, showed that organized nutritional care provides a good starting point. Moreover, the mobile application MalNut, which combines various evidence-based methods for diagnosing malnutrition and cachexia, simplifies the assessment process of the degree of malnutrition and cachexia in hospitalized patients and the elderly. The application offers possibility for further differentiation between malnutrition risks and different forms of manifest malnutrition. In addition, it can be easily applied in other clinical settings and elderly homes to support the first step toward developing a comprehensive nutritional care protocol within the framework of the hospital accreditation process. Clearly, a larger study involving a larger group of different patients as well as more hospitals and elderly homes are needed to confirm the outcome of this survey in Slovenia.