Conducted under the auspices of the Italian Society of Consultation Liaison Psychiatry (SIPC) the aim of this study was to describe the characteristics of Consultation Liaison Psychiatry (CLP) activity in Italy (SIPC-2—2018) over the past 20 years by comparing with data from the first Italian nation-wide study (SIPC-1—1998).ad hoc 60-item Patient Registration Form recording information from five different areas: Sociodemographic, hospitalization-related, consultation-related, interventions and outcome.We collected data on CLP visits of 3,943 patients from 10 Italian hospitals over a period of 1 year. Data were compared with those from the SIPC-1 1998 study . Patients were assessed with the same d = 0.54) and hospitalized for a longer duration (d = 0.20). The current study detected an increase in the proportion of referrals from surgical wards and for individuals affected by onco-hematologic diseases. Depressive disorders still represented the most frequent psychiatric diagnosis, followed by adjustment and stress disorders and delirium/dementia. Also, CLP psychiatrists prescribed more often antidepressants (Φ = 0.13), antipsychotics (Φ = 0.09), mood stabilizers (Φ = 0.24), and less often benzodiazepines (Φ = 0.07).Compared with participants from the previous study, SIPC-2-2018 participants were significantly older (CLP workload has increased considerably in the past 20 years in Italy, with changes in patient demographic and clinical characteristics. A trend toward increase in medication-based patient management was observed. These findings suggest that the psychiatric needs of patients admitted to the general hospital are more frequently addressed by referring physicians, although Italian CLP services still deserve better organization and autonomy. Consultation-Liaison Psychiatry (CLP), as the subspecialty of psychiatry liaising with other branches of medicine and stemming from the realization that some form of psychiatric comorbidity is evident in more than one third of patients admitted to the general hospital (GH) , 2, haveThis reflected a general interest in the CLP subspecialty at a European level, as evident from the involvement of international groups such as the European Consultation-Liaison Psychiatry Working Group (ECLW)  that led1 was created with the aim to promote a nationwide research project on a 1-year period to better analyze the CLP situation in Italy  coefficient as measures of statistical robustness, while percentage difference (PD) and mean difference (MD) were calculated as measures of absolute differences between the variables of interest. Statistical analyses were performed using SPSS —20 package. To aid visual comparisons, appropriate figures and graphs were created using ggplot R package.Descriptive statistics were conducted using bivariate analysis. Differences in estimates between the samples were explored using 2 = 2791.75, df = 10, p < 0.001, V = 0.58).In Study 2 data pertaining to 3,943 patients were collected and were compared to the sample of 4,183 patients of Study 1. The distribution of the consultations at both times according to the region of provenance are shown in d = –0.54). Data regarding age according to sex and the distribution of age according to psychiatric and somatic diagnoses are displayed in Socio-demographic characteristics are shown in Data pertaining to somatic diagnoses regarding referred patients are presented in p > 0.05).When comparing reasons for psychiatric referrals in Study 1 with Study 2, statistically significant changes were evident for the following reasons: Study 2 patients were more likely to be referred to psychiatric assessment for pharmacologic treatment , suicide risk , problems in patient’s management or compliance  or the presence of active psychopathological symptoms ; they were also less likely to be referred for pregnancy issues , medically unexplained symptoms  and alcohol or substance abuse  . PsychiaPatients were informed more often about psychiatric consultation referral in Study 2 with respect to Study 1 .p > 0.05, Φ = 0.00), although the pattern of mental health care in Study 2 patients was more prevalent in terms of psychiatric care at mental health outpatient services  and psychiatric private practice , and less prevalent at other services . Also, Study 2 patients reported a lower number of hospitalizations in psychiatric units in the previous 5 years   .d = –0.23), while the time from referral to consultation (Lagtime 2) was significantly lower than in the Study 1 . Study 2 patients received slightly fewer follow-up visits during the hospital stay , with shorter consultation time  and longer hospitalization length   was significantly higher in Study 2  .Patients in Study 2 were more likely to be already treated with psychopharmacologic medications at the time of consultation than in Study 1 , especially with antidepressants , and mood stabilizers , but also with antipsychotics  and benzodiazepines  .p > 0.05) between the 2 groups  and consisted of more frequent diagnosis of depressive disorder , bipolar disorder , behavioral syndrome due to delirium or dementia , and other disorders . Study 2 patients received less often a diagnosis of personality disorder , anxiety disorder , schizophrenia  or somatoform disorders , while adjustment disorder and substance abuse disorder did not significantly differ  specifically, antidepressants , antipsychotics  and mood stabilizers  than Study 1, while benzodiazepines were less frequently prescribed  .At discharge, Study 2 patients were less likely to receive psychopharmacologic treatment than Study 1 ; overall in Study 2 antidepressants , antipsychotics , and mood stabilizers  were prescribed more frequently while the prescription of benzodiazepines was lower  .p > 0.05), while in Study 2 patients were less frequently recommended to be transferred to other medical wards  , with patients being referred more often to social workers  and other specialized services  and less frequently to their general practitioners , psychiatric outpatient services , consultation-liaison services  and private practitioners . Psychiatric hospitalization rates did not differ between the two groups ( = 0.03) .We report the results of a nationwide multicenter study describing CLP activity in Italy on almost four thousand patients, and comparing them to results from a previous CLP study adopting the same methodology of data collection carried out 20 years ago.A first general result of the study is the increase of the ages of nearly a decade of the patients referred to CLP between the two studies. This finding seems to be in line with the general aging of the Italian population over the last 20 years and the increased life expectancy in Italy , as indiA second finding regards psychiatric referrals. Compared Study 1, patients in Study 2 were referred more often from surgical wards. A possible explanation might include a better understanding and more education about the importance of psychiatric variables by surgeon colleagues, as highlighted by increasing literature in the surgical field –33. AlteStudy 2 patients were also more likely to be referred from hematology-oncology settings. The almost quadrupled number of referrals for patients affected by these diseases reflects the important work done in the last two decades in the field psycho-oncology, with data showing a prevalence of psychiatric disorders in cancer care of 25–32% , 37. ThiA striking result is the lower rate of referrals for patients reporting MUS as the main reason for psychiatric evaluation and the low prevalence of somatoform disorders diagnosis in Study 2. There are different possible explanations for this finding. The first might be related to improvement in diagnostic tests , better understanding of these disorders, and improved education and management skills by non-psychiatrists, including rheumatologists, gastroenterologists and neurologists who have learned to treat common comorbidities like depression and anxiety . We cannRegarding psychiatric diagnosis: the rates of adjustment and stress disorders, depressive disorders, and alcohol and substance abuse were comparable across the two studies. Depressive disorders still represent the most frequent psychiatric diagnoses, reflecting their high prevalence in the GH  and a geFurther findings regard the length of stay, Lagtime1 and Lagtime2. Interestingly, while Hospitalization Length and Lagtime1 significantly increased in Study 2, Lagtime2 decreased. This last result probably indicates an overall improvement in the effectiveness of Italian CLP services, with psychiatric consultants able to deliver quicker visits. Increased Lagtime1 and hospitalization length can be interpreted in the light of the aging of the sample, since both age and Lagtime1 have been found to be predictors of Hospitalization Length –71 and, Considering drug prescriptions, at the time of consultation patients were more likely to be already receiving psychoactive drugs, particularly antidepressants, mood stabilizers and benzodiazepines, compared with the previous study wave. CLP consultations resulted in an increase of antidepressants, antipsychotics and mood stabilizers prescription compared with 1998, and a relative decrease of benzodiazepines prescription. This pattern was relatively maintained at discharge, with a further decrease of benzodiazepines prescription in line with recent guidelines . With reFinally, interesting differences were shown in the type of consultation and liaison interventions. While in Study 2 there was only a very small decrease in liaison intervention at discharge, compared to Study 1 there were significant changes in referral patterns, with comparable rates of psychiatric inpatient admissions. A first issue comes from the increased referral to social work services, which could be explained by a grown awareness of the importance of the social component of the problems presented by patients, especially if affected by somatic diseases –85 and iRegarding the post-discharge plan, patients in Study 1 were more often referred to specialized services . This seems to support the implementation over the last 20 years of more special services within community psychiatry and an improvement of the organization of mental health services in Italy.The study is strengthened by adequate sampling and nationwide participation. There are, however, limitations which should be mentioned. First, although there is a similar characterization and representation of the CLP services included in both Study 1 and 2, there are also differences in regional participation, such as a higher presence of Northern Italian centers in Study 2. Future studies should include a larger sample of centers and extend the research to a larger representation of GHs, including CLP activity in small community hospitals, which are under-represented in CLP studies in several countries . For theIn conclusion, this study provides information about the current status of CLP in Italy. The data presented here confirm a predominant consultation-based approach to the psychiatric care of the medically ill patient in Italian GHs. The changes over time discussed in this article may support a more proactive approach in the provision of CLP services, and more consistent to relevant changes in the epidemiology of medical-psychiatric comorbidity; also, we hope they could guide future research on the topic and pave the way for structural changes in the delivery of care for the patient affected by psychiatric and somatic co-morbidities.The datasets presented in this article are not readily available because of its proprietary nature. Requests to access the datasets should be directed to the corresponding author.The studies involving human participants were reviewed and approved by the Ethical Committee for the Protection of Persons as adopted by the University Hospital and Hospital Local Health Trust of the participating centers. The patients/participants provided their written informed consent to participate in this study.The following persons participated as local coordinators of the Italian C-L Psychiatry working Group:1,2, Emilio Bergamelli3, Victor Attilio Campagna3, Melissa Cherubini1,2, Federica Folesani4,5, Marta Gancitano4,5, Francesca Giannetti6, Gianluca Giovanna7, Benedetta Gullotta4,5, Lucia Massa8 and Giulia Montardi1,2Jessica Bellucci1Section of Psychiatry, Department of Diagnostic-Clinical Medicine and Public Health, University of Modena and Reggio Emilia, Modena, Italy, 2Dipartimento ad Attività Integrata di Salute Mentale e Dipendenze Patologiche, USL-IRCCS di Reggio Emilia, Reggio Emilia, Italy, 3Department of Health Sciences, Università Degli Studi di Milano, Milano, Italy; Department of Mental Health, ASST Santi Paolo e Carlo, Milan, Italy, 4Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy, 5University Hospital Psychiatry Unit, Integrated Department of Mental Health and Addictive Behavior, University S. Anna Hospital and Health Trust, Ferrara, Italy, 6Psychiatric Operative Unit n.25 of Casalmaggiore (Cremona), “Oglio Po” General Hospital, Cremona, Italy, 7Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy, 8Department of Clinical and Experimental Medicine, Psychiatric Clinic, University of Pisa, Pisa, Italy.LG, LZ, MBe, and SF conceived the research. LZ, RC, MN, MR, MBa, AD’A, AM, MP, IT, LP, SP, PM, SF, and TT contributed to data collection. LZ carried out the statistical analysis and wrote the first draft. All authors contributed to the manuscript and approved the final version.


Acquired haemophilia A (AHA) is a rare bleeding disorder caused by inhibitory autoantibodies against coagulation factor VIII (FVIII). AHA is a disease that most commonly affects the elderly but has also been observed in children and in the postpartum period. AHA is idiopathic in 50% of cases and is associated with autoimmune diseases, malignancies, and infections in the remaining 50%. Recently, cases of association between AHA, COVID-19 vaccination, and infection have been reported in the literature. For diagnoses, determining FVIII levels is crucial to distinguish the different causes of aPTT prolongation. Treatment of AHA is based on bypassing agents  and porcine FVIII to control the bleeding and immunosuppressive therapy  to suppress autoantibody production. It is important to start a prophylactic regimen to prevent further bleeding episodes until the inhibitor is negative. Recently, the series of cases reported in the literature suggest that emicizumab may provide effective and safe haemorrhage prophylaxis in the outpatient setting. Acquired hemophilia A (AHA) is a rare hemorrhagic disorder caused by the spontaneous development of inhibitory autoantibodies against the clotting factor VIII (FVIII) . AHA hasThe clinical impact of AHA is higher because the severity of bleeding is affected by diagnostic delays and inadequate treatment .Diagnoses are often delayed because the rare condition goes unnoticed by medical doctors unfamiliar with the disease ,13. MostThe management of AHA has two major goals: control bleeding by achieving adequate haemostasias and the eradication of the inhibitor ,16. WhilPapers were found following a comprehensive search in PubMed, Google Scholar, and Scopus using the following terms for the treatment and diagnosis of the AHA, without time limits, and using the English language as a filter: “acquired haemophilia A”; “treatment”; and “diagnosis”. To collect papers about COVID-19 vaccines and hemophilia A, we used the terms “haemophilia A”, “COVID-19”, and “vaccination”. For emicizumab use, we used “Emicizumab” and “acquired haemophilia A”. The references of all retrieved original articles and reviews were assessed for additional relevant articles.A total of 50% of AHA cases are idiopathic and 50% are associated with underlying medical conditions, such as autoimmune disease, malignancy. and infection, during the postpartum period as a side effect of certain drugs and vaccinations ,19,20,21In p = 0.05) and days of hemostatic treatment (7.6 (SD = 5.7) vs. 23.8 (SD = 13), p = 0.003) [The rapid diagnosis and prompt treatment of bleeds are crucial to optimize the treatment of AHA ,11. AHA = 0.003) . The ble= 0.003) ,46,47. T= 0.003) . The fol= 0.003) ,46. GastClinical manifestations do not always correlate with the level of FVIII and the titer of the inhibitor. Due to the different types of kinetics for acquired hemophilia (non-linear) compared to congenital hemophilia (linear), the inhibitor level may underestimate the inhibitor effect . HoweverStop bleeding.Prevent others by eradicating the inhibitor and the clone responsible for its production.Treat, if identified, the underlying cause.The treatment, therefore, has a three-fold objective:The speed and appropriateness of the treatment and management are crucial. In the presence of hemorrhagic events, treatment aims primarily to control the acute bleeding quickly and eradicate the inhibitor, minimizing the risk of recurrent bleeding, which persists if the anti-FVIII inhibitor is present. While treating acute bleeds is a key priority in AHA care, not all patients bleed, and not all bleeds require intervention ,11,50. PInternational guidelines suggest treating the injury caused by the bleeder’s disease as quickly as possible in first-line therapy with bypassing agents, such as activated coagulation factor complicated concentrate (aPCC) or activated recombinant FVII, or with recombinant porcine FVIII ,53,54,55Data from the EACH2 registry also show that rFVIIa was the most widely used hemostatic agent, with an efficacy of 92% . The eff®, Baxalta Innovations, Vienna, Austria; now Takeda) is documented by numerous case reports and a retrospective study of 34 patients in whom bleeding resolution occurred in 86% of cases [The effectiveness of aPCC  can produce detectable FVIII levels and hemostasis in AHA. Based on a prospective study in adults with serious bleeding, recombinant porcine FVIII  was approved for the treatment of bleeding in AHA in the United States, Canada, and Europe . All 28 2 weekly times 4, alternative 100 mg weekly times 4) [Traditional hemostasis should be achieved right away, and matter destruction should be quickly performed with corticosteroids alone or with corticosteroids and cyclophosphamide. If these counselled treatments fail or are contraindicated, patients should be treated with rituximab. Even with minor bleeding, patients are at risk for significant and fatal bleeding, regardless of initial factor VIII levels and inhibitor titers. Therefore, treatment guidelines recommend that patients receive immunosuppressive therapy immediately after diagnosis to eliminate inhibitors and normalize factor VIII levels ,16,65. Ftimes 4) . They untimes 4) . Tiede Atimes 4) .p-value = 0.0016). The mean number of days in prophylaxis after major bleeding was 12.7 (SD = 5.7) and the mean aPCC prophylaxis dose was 54.2 IU/kg (SD = 23.0) [®, also known as ACE910) is a recombinant, humanized, and bispecific monoclonal antibody that resembles the activity of FVIII. Emicizumab has a convenient pharmacokinetic profile due to its suitable subcutaneous administration route and has become interesting in the treatment of haemophilia A in patients who have or do not have inhibitors [There is therefore a risk of recurrent severe bleeding until the inhibitor is eradicated . Baudo e = 23.0) . Recentlhibitors . Efficachibitors ,67. The hibitors ,69. In chibitors .The cost of emicizumab remains the single most significant barrier to its use in developing and developed countries. Multiple studies have shown that bleeding prevention with emicizumab is more cost-effective than bypassing agents ,68. To pKnowledge about the recognition and treatment of acquired hemophilia A has improved in recent decades. Laboratory information allows clinicians to gather information to refine the diagnosis by eliminating confounding factors.Currently available drugs, if used appropriately, can adequately control bleeding, even in emergencies. New pharmacological and care approaches make it possible to prevent bleeding up to inhibitor negativization and manage the patient at home. In addition, vaccination and COVID-19 infection have been reported as new causes of acquired hemophilia, but further clinical data are needed for confirmation.


Saccharomycetales are ascomycetic yeasts and, amongst them, the genus Blastobotrys has approximately 30 known species. Blastobotrysmalaysiensis is a yeast species, described from cave samples, known until then only from Malaysia. In this study, we characterise a new strain and report the second occurrence record of this species. Here, Blastobotrysmalaysiensis URM 8507/SXS 675, was collected from sediments samples from a cave in the Parque Estadual de Terra Ronca (PETER) in Goiás, Brazil. Phylogenetic analyses revealed strong support with the sequence of the species type, as well as with other species of the clade. This new record contributes by providing new molecular data for the species and expanding the knowledge of its distribution beyond the Asian continent.First record of a yeast for the American continent and its second mention for the world. Saccharomycetales comprises the ascomycete yeasts, with about 1000 described species. They can be found in various niches, either as saprotrophs, in mutualistic associations with plants and animals and even as pathogens (The order athogens .BlastobotrysKlopotek (1967) is a genus of this order and has approximately 30 known species. The genus is characterized by the presence of setae, such as cell wall projections, micropores in the septa, central micropores and the formation of blastoconidia that form in denticles. Dimorphism is also observed in several species of the genus and can be found either as a filamentous structure (mycelium) or in yeast-like growth (unicellular), with different dimorphic mechanisms for each species , also presenting the genus Trichomonascus as an ascosporic state (Kurtzman and Robnett 2007). Also, phylogenetic data showed that Blastobotrys, Sympodiomyces, Arxula and some Candida species correspond to a single genus, defined as Blastobotrys and that species of Arxula and Sympodiomyces should be transferred to Blastobotrys , located in the Terra Ronca State Park (PETER), in the municipality of São Domingos, far east of the state of Goiás, bordering the state of Bahia, Brazil Fig. , formed The PETER covers three Brazilian regions and its predominant biome is the Cerrado. The area comprises 57,000 hectares, with a climate of type AW , with cold and dry rains in winter and hot humid summers and average annual precipitation of 1,500 mm . PETER h1). The plates were sealed with film paper and transported to the laboratory of Basic, Applied and Scientific Dissemination Mycology (FungiLab) of the State University of Goiás, Central campus, where they were incubated at 28℃, the temperature verified in the cave during isolation, in aerobiosis for seven days. Grown colonies were isolated and purified on Potato-Dextrose-Agar (PDA) medium.The specie reported here was isolated from sediment samples from Lapa do Angélica Cave, specifically from the aphotic zone, with only one strain. We observed that, in these sediments, there were signs of bat guano, in small quantities. The isolation was performed by contacting the swab soaked in sterile saline solution (0.9%) with the sediment and then streaked on Petri plates containing medium Sabouraud (Sa) Agar, increased with chloramphenicol  broth and incubated under constant agitation (130 RPMs) at a room temperature (± 28℃), to be used in the assimilation and fermentation experiments. In addition, inocula from the pure colony were subjected to growth at different temperatures  and in different culture media, such as PDA, Malt Extract Agar (MEA) and Mycosel Agar, the latter being used to verify resistance to cycloheximide. For morphological characterisation, light microscopy (OLYMPUS CX31) was performed using cotton blue lactophenol and sterile water to prepare the slides, where it was possible to observe the microstructures. The purified colonies were stored in mineral oil and deposited in the culture collections of the URM Micoteca (URM 8507) and the ueg FungiLab, under voucher SXS 675 using the Castellani method.B.malaysiensis was inoculated in 5 ml of basal medium (Peptone and Yeast extract) increased with 2% of each sugar (carbon source) and incubated at 27 and 30℃ for 8 days.The assimilation and fermentation tests were performed with five sugars: xylose, glucose, maltose, lactose and galactose. The isolate of The assimilation of the carbon sources was considered positive when the presence of cell mass was observed, verified according to the concentration of cells, through the optical density spectrophotometric method (OD 600). For the fermentation test, the Durham tube technique was used, being considered positive fermentation when half of the tube was filled with gas.For taxonomic identification, a 0.5 ml of cell mass was collected from the culture in YPD broth and submitted to DNA extraction using the CTAB method . After gBlastobotrys, according to , shown in Table rding to . The newWe used two different analyses, Maximum Likelihood (ML) and Bayesian Inference (BI). ML was performed from TOPALi v.2  determinEnter subsection textKurtzman, 2007B0E84A0E-5CE8-5458-BDD3-35D52E4D7991Type status:Other material. Occurrence: occurrenceDetails: Isolated from cave sediments; recordNumber: URM 8507/SXS 675; associatedSequences: MZ702867; occurrenceID: 0CC4B08A-70E3-5DE6-9209-1F6A530E0BBF; Taxon: order: Saccharomycetales; scientificNameAuthorship: Blastobotrysmalaysiensis Kurtzman, 2007; Location: higherGeography: South America: Brazil: Goiás: Parque Estadual de Terra Ronca; continent: South America; country: Brazil; countryCode: Brazil/BR; stateProvince: Goiás; municipality: São Domingos de Goiás; locality: Cave Lapa do Angélica; decimalLatitude: -13.5173; decimalLongitude: 46.388077; Identification: identifiedBy: Sá-Ferreira A.S., Leonardo-Silva, L. Xavier-Santos, S.At five days of growth at 25, 28 and 30℃, in PDA medium, the colony showed opaque white colouration, with a mycelial fringe and lobed margin; when growing in MEA, at 27ºC, yellowish colony, with cottony aerial mycelium in the centre and dense and opaque margin was observed. In both media, growth of septate hyphae and pseudohyphae was noted. In MEA medium, in samples from the margin of the colony, abundant spherical cells (2.74 - ˗4.50 µm) with multilateral budding were observed   showed strong support  clustering close to the type species (CBS10336), with 100% similarity.The dataset included sequences from 20 yeast species that are related to the B.malaysiensis (URM 8507/SXS 675) also showed resistance to cycloheximide, as well as growth at 37°C and 40℃. This thermotolerant characteristic is well understood and observed in several species of the genus, which makes it considered biotechnologically promising (B.malaysiensis to ferment glucose. We observed that the strain fermented little of this sugar under the conditions presented, corresponding to less than half of the gas occupying the Durham tube.As verified by romising . The ferThe strain reported here was isolated in the cave's resurgence, an area that is not open to tourists, as it is difficult to access. This access is made either externally, through a 10 km trail in a dense forest or internally, through the river inside the cave, a route that presents great obstacles, considered very dangerous by regional guides and the speleological community. For this reason, it is an environment that has suffered little impact from human visitation.Some hypotheses may explain how this yeast was dispersed to this specific environment since, until now, it was only reported occurring in a cave environment in Malaysia. B.malaysiensis is a troglobic yeast, despite only being known in cave environments, but we emphasize the importance of further research efforts involving this species, to elucidate its current distribution. Whether it is a species restricted to subterranean environments or if this current distribution is only due to the lack of sampling and precise taxonomic identification. The present study reports the second worldwide occurrence of B.malaysiensis, expanding its distribution beyond the Asian continent.Thus, we cannot assume that


Thegrowth process of metal–organic framework (MOF) nanocrystalsdefines their properties and functions. However, defects may be prevalentduring the crystallization of even seemingly perfect MOFs, such aszeolitic imidazolate framework-8 (ZIF-8), and yet direct probing ofsuch structural defects has been challenging because of the lack ofnanoscale techniques to locally examine individual nanocrystals. Here,we directly study local defects, such as missing linkers or metalvacancies, in ZIF-8 nano- and microcrystals with near-field IR nanospectroscopycombined with density functional theory calculations. We track thechemical changes during crystallization and show that structural defectslike zinc cations that are bound to molecules of the reactant graduallydisappear with ripening of the crystals, while dangling and missinglinker defects prevail. The resulting defect-terminating groups oropen-metal sites produce mechanical anisotropy and reduce the Young’smodulus, as measured via tip force microscopy with nanoscale resolutionand supported by theoretical modeling. However, these structural defectsalso open the door for defect engineering to tune the performanceof ZIF-8 by offering additional adsorption sites for targeted catalyticreactions, chemical sensing, or gas capture. Their diversity gives riseto their vast physical and chemical properties, paving the way forapplications in sensing technologies, drug delivery, gas capture,or catalysis, among others.9 Because the nucleation is driven by random fluctuations in the bulksolution without dedicated nucleation sites, little can be done totailor this mechanism. The crystal growth, on the contrary, can bemanipulated by changing the molar ratio of reactants, amount of solvent,and other stimuli to yield crystals with the desired sizes and shapes.Indeed, several studies have scrutinized the impact of the growthtime, temperature, or use of different modulators on the formationof ZIF-8 nanocrystals by employing techniques such as atomic forcemicroscopy (AFM) or scanning electron microscopy (SEM) combined withdiffraction or adsorption–desorption analysis to capture thesize distribution, shape, and crystallinity of the crystals.15In particular,the formation of ZIF-8 crystals, or MOF crystalsin general, can be divided into nucleation and growth 1.9 Becau16 Defect engineeringopens pathways to locally tune the intrinsic porosity, create openmetal sites, and modulate the surface properties of MOFs, which hassignificant implications for separation, gas capture, catalysis, andmechanical responses.25 Perhaps the model system for defective MOFs is UiO-66 (Universiteteti Oslo); here, nanoregions of ordered defects had been reported, whichinspired detailed studies on the defects and their effects on thematerial.29 For instance, structural defectsin UiO-66 were observed using a combination of low-dose transmissionelectron microscopy (TEM) and electron crystallography, further confirmingthe increased catalytic activity for defective structures.30Yet, if seen in the context of controlling the material properties,another factor plays a crucial role in crystalline nanomaterials:the presence of defects.31 Hitherto, only the feasibility of local defectsin ZIF-8, such as linker and metal vacancies or dangling linkers,has been predicted by computational modeling.33 However, despite that fact that a few other studies have focusedon the implications of defects in gas separation34 and storage35 or found surface-terminatingdefects,36 many open questions remain.One might ask, do defects occur and transform during crystallizationof ZIF-8? Also, to what extent do the defects affect the propertiesand, as such, the performance of the material for potential applicationsincluding gas capture, chemical sensing, and catalysis?Little is known, in contrast, about defectsin ZIF-8; this maybe partly because this material is considered to be among the moststable frameworks, but while this is true, it is, in fact, very plausiblethat defects or other irregularities may occur during the crystalgrowth process, possibly with a significant impact on the performanceof the materials, and its subsequent long-term stability.41 Previously, we demonstrated the capability of this technique toprobe individual MOF-type nanocrystals, such as ZIF-8, opening thedoor for discovering their previously unreported characteristics froma new perspective: at the single-crystal level.39 Compared with conventional techniques, this nondestructiveapproach allows not only direct imaging but also simultaneous measurementof the sample’s properties including chemical information orphysical properties at a resolution akin to AFM.40 For instance, the mechanical properties can be obtainedwith the same setup, albeit operated in contact mode instead of tappingmode. In these tip force microscopy (TFM) measurements, a force–distancecurve is attained from every pixel of the AFM scan by retracting theAFM tip, measuring the required force to do so. The local stiffnessis then determined from the force difference between the maximum forceand the reference trigger point on the curve.42 From the measured stiffness data of a sample surface, an image ofthe Young’s modulus map can be derived. By simultaneous measurementof the shape, size, chemical composition, and mechanical propertiesat the nanoscale, using a suite of multimodal near-field techniques—s-SNOM,nanoFTIR, AFM, and TFM—allows us to shine new light on thegrowth process of the ZIF-8 nanocrystals.To answerthese questions, we employ scattering-type scanning near-fieldoptical microscopy (s-SNOM), merging AFM with IR spectroscopy to enablenear-field IR nanospectroscopy. It is this combination that can unravelthe fine-scale features, mechanisms, and chemical interactions ofMOFs at the nanoscale by yielding a Fourier transform infrared (FTIR)spectrum of a local 20 nm spot.ab initio density functionaltheory (DFT) calculations through a comparison between ZIF-8 idealand defective model structures.In this study, weexplore how defects transform during crystallizationof ZIF-8, further elucidating their impact on the mechanical propertiesof the material. First, we study ZIF-8 nanocrystals before turningto microcrystals, obtained through two different synthesis routes.To examine the intermediate steps of the crystallization, the crystalgrowth was stopped after 1, 3, and 60 min by removing some materialfrom the same batch and performing three washing steps. The experimentalevidence was corroborated by 3)2·6H2O at 824, 1042, 1128, and 1315 cm–1 in the nanoFTIRspectrum .8 Here, the high intensity of the (110)peak at 7.3° is attributed to the formation of ZIF-8 with a regularrhombic dodecahedron morphology, which resembles the final stage ofthe growth of ZIF-8 crystals.14 Small variations,however, can be detected, such as the absence of the (125) peak at28°, or a changing relative intensity of the (110):(211) planes,corresponding to the two most intense diffraction peaks. Albeit minimal,a rise in the intensity of the (110) plane, accompanied by a narrowingof the full width at half-maximum (fwhm) from 0.299 to 0.288, is observedupon prolonged crystallization . Either this can be attributed to the particle size effects viathe Debye-Scherer equation or, given that the increase in the averagesize is minimal , this may indicatea stronger long-range ordering, thus implying a higher crystallinity.44 At first glance, these findings are in goodagreement with the previously reported result, where the crystallinityincreased with the synthesis duration due to the Ostwald ripeningprocess.15 It has been suggested that 5 min was insufficientto grow ZIF-8 crystals,13 but here, paradoxically,it is the marginal increase of the crystallinity, and the ATR-FTIRspectrum of the crystals with 3 min growth time, which matches thatof the final growth stage, that indicate the completion of the self-assemblyof ZIF-8 nanocrystals after only 3 min.15After a growth time of only 3 min, the ZIF-8 nanocrystals havealready formed, as confirmed by comparing their X-ray diffraction(XRD) pattern and attenuated-total-reflectance (ATR)-FTIR spectrawith those measured on crystals after a growth time of 60 min 3a,b. In 3)2·6H2O, with its characteristic peaks around 824 and 1042 cm–1 associated with the stretching modes of the NO3– anions  and the mImlinkers (745 cm–1), further uncovering local defectsassociated with the linker, such as a partially coordinated linkeror a dangling linker, as the termination units close to the crystalsurface . This leads to the conclusionthat structural defects, such as the different crystal lattice terminations,are gradually disappearing with prolonged crystallization.Turning even more locally, individual point spectrashow the superpositionof peaks assigned to ZIF-8 is measured at every pixel of the scan, while simultaneously imagingthe topography at nanoscale resolution. In that way, the local stiffnessof the sample under investigation is acquired with a resolution akinto AFM imaging  have been filtered out beforethe mean stiffness of the nanocrystals is derived  = 1.7 ± 0.7 GPa (or between 0.8and 3.4 GPa considering nine different scans), which is lower comparedwith the stiffness of the crystals at the final growth stage whenit was determined that E(60 min) = 2.1 ± 0.5GPa . Likewise, the crystals with short crystallization unveilmore variance in the local Young’s moduli, even revealing abimodal distribution (S6). A simple way of puttingthis is to say that higher crystallinity, and thus stiffness, is achievedwith prolonged crystallization, but there is more to it than that,especially because the increase in crystallinity is marginal, as discussedearlier. An alternative explanation might be to suggest that the observedstructural defects, whether they are different termination units,uncoordinated metal clusters, or dangling linkers, introduce localdisturbance to the otherwise periodic bulk structure and thus disruptthe stability of the framework as a whole; in other words, one mightdescribe them as local disorder with a far-reaching impact. This appliesparticularly to the mechanical properties due to their dependenciesupon the long-range order of the crystal. The observed phenomenonthat the local structural stiffness of the framework, or the mechanicalstability of crystal in general, is lowered with increasing defectlevel coincides with previously reported simulations, where the elasticconstants were calculated for defective UiO-66 crystals; however,the assumption that defects in ZIF structures lead to different mechanicalproperties demands further proof.51Of course, thedifferent termination units, the undercoordinatedmetal, and the dangling linker all invite the question of how andto what extent they might influence the properties of the nanocrystals,which are so intrinsically linked with the framework assemblage, arrangementsof the functional groups, and characteristics of the pore. Even ifonly slightly, defects may affect the material’s stabilityby disrupting the crystalline order of the framework material, butwhether the relationship between the defects and their impact on thematerial performance can be precisely established remains to be studied.Because of the lack of other experimental techniques to probe themechanical properties of individual nanocrystals, this is best donewith TFM, where the Young’s modulus  imaging 4.42 It i derived 4a,b. Theribution 4a and S6CRYSTAL17 code48 to compute the elastic tensors Cij for three different structuresof ZIF-8: first, the ideal defect-free crystal was simulated usingthe PBEsol0-3c method.52 Derived from thisideal unit cell, the missing zinc defect was introduced as a zincvacancy and by the replacement of two N–Zn bonds with N–Hbonds, thereby creating dangling or undercoordinated linkers. Thethird system, which, in turn, simulates the missing linker defect,was attained by removing a linker group, while an associating waterand the conjugate base of the proton-donating group filled the twounsaturated metal sites. Visualizing the elastic representation surfaces reveals the differencesin the mechanical properties due to defects, corroborating the trendsderived from the experimental findings. As shown in 54 On the contrary, with the introduction of a missing zinc defect,an anisotropic behavior is revealed. The anisotropic mechanical responseof ZIF-8 has previously been investigated, e.g., as a function ofthe pressure,54 but in this work, we focuson the impact of point defects on the mechanical properties.Hence, we performed DFTcalculations with the surfaces4c and thIn the case of missing zinc defects, although the maximum stiffnessin the direction of the stable, undisturbed zinc bonds is akin tothat of the perfect crystal, the minimum Young’s modulus issignificantly smaller 4e. If fo51 On the question of anisotropy, it is worth mentioningthat anisotropy is linked to the distribution of defects along givendirections. The calculations assume a periodic occurrence of the introduceddefects, while, in reality, the number of defects and their orientationis, most likely, random. Yet, even if only one defective site is modeledper unit cell to preserve a mechanically stable system, the defectis replicated throughout the entire crystalline structure becauseof periodic boundary conditions. Therefore, the DFT models translateto the single-crystal level when the elastic constants are computed,enabling us to make the link to experiments. However, although thesimulations predict the mechanical properties of the defective ZIF-8systems under investigation and the local measurements confirm thecorresponding decrease and anisotropy in stiffness, it remains challengingto distinguish between the type or location of defects from thesenanoscale measurement techniques.The theoretical results above can explain the observedcharacteristicsof the local stiffness measured with TFM: the average stiffness and,as such, the material’s stability are generally reduced inthe defective structures. If inverted, the effect is that the structuralflexibility, adsorption, or other anisotropic responses to externalstimuli can be enhanced in an otherwise “rigid” MOF(greater stiffness) by introducing structural defects.Figure S5 for a complete scan of the crystals). First, thenanoFTIR spectrum corresponding to the longer growth process showsa better match with the calculated spectrum of an idealized, periodiccrystal because, with prolonged crystallization, the number of idealbonds increases, and thus the positions and intensities resemble thecalculated IR spectrum. Second, a detailed study of the individualvibrations, considering the DFT calculations as well as the nanoFTIRspectra of the reactants before synthesis, gives insights into boththe structural and chemical changes happening during crystallizationof the 3D framework. The pronounced peak at 758 cm–1, for instance, correlates with the symmetric out-of-plane bendingof the mIm ring and associated motions of the H–C=C–Hbond present in the framework structure 2·6H2O], which is not expected to appearafter the construction of ZIF-8, where both reactants are used upentirely to form ZIF-8 crystals. However, because the vibrationalmode associated with the NO3– stretchingis still present in the nanoFTIR spectrum, the crystals formed afteronly 5 min still contain residuals of excess reactants, thus suggestingthat some metal clusters are not fully coordinated with the mIm linkers.Additional observationsare made by tracking the changes in key vibrational bands during thecrystallization of ZIF-8 microcrystals, which further reveals howdefects transform. As shown in the SEM images in –1, the vibrational mode associated with the metal reactant at 824cm–1 depicts a reduced relative intensity from 0.74:1to 0.48:1 with a longer crystallization time, a finding that alreadycontains, in essence, everything that has been observed for the nanocrystals.With prolonged growth time, the defects of ill-terminating metal clustersthat are bound to molecules of the reactant gradually disappear. Thesame phenomenon is revealed in the reduction of the less pronouncedpeak at 1042 cm–1; likewise, this peak simultaneouslyvanishes as the complete framework is assembled  can be detected at such localscales. In particular, the vibrational mode at 1115 cmibration 5c.–1—the latter is attributed to the C–Hrocking and ring stretching in the framework—reveals the defectof unsaturated, ill-terminating ligands, or so-called dangling linkers,which are only bound to one zinc atom. As a result, the free-spacevibrations of the linker, particularly the mode associated with theunwieldy asymmetric ring stretching and the N–H bonds, areenhanced and thus detectable in the nanoFTIR spectrum. Once boundto two zinc atoms in a fully assembled framework, these motions aremostly constrained, as indicated by the disappearance of this mode,or the decrease in the relative intensity to 0.47:1, with prolongedcrystallization. In fact, the DFT assessment shows that this asymmetricring stretching mode is even more suppressed in a defect-free crystal,as implied by the low relative intensity between the two simulatedpeaks (0.05:1). This suggests that, to some extent, this type of defectis found to prevail even when the final stage of the microcrystalgrowth is reached after 60 min. One can thus conclude that ordereddangling linker defects can exist in ZIF-8 microcrystals, includingthose deemed seemingly perfect.Thus, inthe 5 min crystallization, the high relative intensityof this vibration with 0.85:1 compared with the ZIF-8 peak at 1146cmFigure S12), the local nanoFTIR spectra do not. Instead, itis possible to pinpoint local characteristics in the vibrational modesand, in combination with computational modeling, associate them withchemical and structural peculiarities at the nanoscale. A glance atthe vibrations between 1250 and 1350 cm–1 will furtherillustrate this because these additional vibrations are observed inthe local spectra of ZIF-8 crystals and can be assigned to missinglinker defects, yet they appear neither in the ATR-FTIR measurementnor in the calculated crystal, which is defect-free . This novel tool can thus spark the explorationof local defects, not only in MOFs but also in other crystalline nanomaterials.In particular, the combination of s-SNOM with theoretical modelingof the mechanical properties unveils the missing link between previousstudies on ZIF-8 that either computationally showed the feasibilityof defects or employed defect tuning for enhancement of the material’sperformance. In addition, the first application of TFM in the fieldof MOFs enables the link to be established between the physical, chemical,and mechanical properties to shed new light on the implications ofdefects or, in fact, any features at the nanoscale. We envisage thatthese findings and techniques invite future studies on defects inMOFs and cognate framework materials either to evaluate the stabilityof “stable” MOFs for targeted application or, on thecontrary, to leverage local defect engineering to tailor the materialperformance.3)2·6H2O; 98%, Sigma-Aldrich]and 13.5 mmol of 2-methylimidazole  in 60mL of methanol, respectively. After the two clear solutions were combined,the white colloidal solution was rigorously stirred for 1 min andthen left to form the nanocrystals. Immediately, some material wasremoved, diluted in fresh methanol, and washed three times. Each washingstep encompassed centrifugation at 8000 rpm for 5 min, followed bysolvent exchange with fresh methanol, and sonication for 30 s. Thesame procedure was repeated after 3, 5, and 60 min: after these timeintervals, some material was removed and thoroughly washed to stopthe growth process.ZIF-8 nanocrystalswere synthesized by dissolving 4.5 mmol of zinc nitrate hexahydrate[Zn(NO3)2·6H2O and 4 mmol of mIm in 40 mL of methanol, respectively.A mixture was obtained by combining the two precursor solutions, whichwas stirred for 1 min and then left to stand. After specific timeintervals , some material was removed from the batchand immediately washed three times with methanol and centrifugation.Two precursor solutionswere prepared by dissolving 4 mmol of Zn(NO3)2·6H2O  or mIm  in methanol,respectively. Likewise, the solution was drop-casted onto a cleansilicon substrate and dried at 80 °C for 30 min.Each samplewas diluted in methanol and drop-casted onto a silicon substrate.To eliminate any excess solvent, the sample was dried in a vacuumoven at 80 °C for at least 30 min. The spectra of the reactantswere measured by dissolving Zn.–1.ATR-FTIR measurements onbulk material wereperformed using a ThermoFisher Scientific Nicolet iS10 FTIR spectrometerwith a spectral resolution of 4 cmSEM images of the samples were obtainedwith a TESCAN LYRA3 electron microscope. Backscattered-electron andsecondary-electron SEM images were obtained at 10 keV under high vacuum.The false-color images were produced using Adobe Photoshop.–1. Demodulation of the optical signalat higher harmonics of the tip resonance frequency eliminated backgroundcontributions to yield the near-field signal, comprising the amplitudeand phase of the scattered wave from the tip. When a pseudoheterodyneinterferometric detection module was employed, the complex opticalresponse of the material was measured, where the real part refersto the nanoFTIR reflectance and the imaginary part depicts the nanoFTIRabsorption spectrum. Each spectrum was acquired from an average of14 Fourier-processed interferograms with 10 cm–1 spectral resolution, 2048 points per interferogram, and 14 ms integrationtime per pixel. The sample spectrum was normalized to a referencespectrum measured on the silicon substrate. All measurements werecarried out under ambient conditions.The near-field optical measurements were performedwith a neaSNOM instrument (neaspec GmbH) based on tapping-mode AFM,where the platinum-coated tip  was illuminatedby a broadband femtosecond laser. The coherent mid-IR light was generatedthrough the nonlinear difference–frequency combination of twobeams from fiber lasers (TOPTICA Photonics Inc.) in a GaSe crystal.Laser A was selected for measurements covering the range from 700to 1400 cm42 Each cycle comprised an approach of the AFM tip from free oscillationuntil the establishment of contact with the sample, followed by subsequentretraction. More specifically, contact was established because ofthe (negative) attractive force between the tip and sample surface.Once in contact, the piezo drove the tip even closer to the sampleuntil the (positive) repulsive force reached a maximum. Upon retractionof the tip, the repulsive force decreased and was replaced by theattractive force because of the adhesion between the sample and tipuntil contact was lost and the tip freely oscillated. From this cycle,various properties could be derived.56 For instance, the topography image was obtained fromthe maximum force, which was fed back to the control circuit to maintaina constant normal force. An adhesion image could be created basedon the maximum adhesion force for each pixel. The local stiffnesswas attained from the force difference between the maximum force anda set point in the repulsive part of the force signal. Hard surfacesled to a larger force difference than that observed for soft surfaces.Calibration measurements were carried out on the silicon substrate,and a polystyrene/poly(methyl methacrylate) polymer blend sample withknown Young’s moduli was used to validate the calibration.The mean local stiffness was obtained from the stiffness images byfiltering out outliers and the background region containing the substrate.The normal and bimodal distributions were then calculated with theintegrated analysis tools in OriginPro 2019.TFM was employedas an additional module to theneaSNOM instrument, but here AFM was operated in contact mode. Thez-piezo driver was modulated at a sinusoidal motion with an amplitudeof 40 mV and a modulation frequency of 610 Hz. A complete force–distancecycle was performed at this rate for each pixel with an integrationtime of 33 ms (200 × 200 pixels per image). The technique followedthe description of a pulsed-force mode.57 It is based on a hybridHartree–Fock/DFT Hamiltonian combined with a double-ζbasis set, augmented with a semiclassical dispersion term and a geometricalcounterpoise correction, which provides a good trade-off between costand accuracy.59 The calculations were carriedout with a development version of the periodic ab initioCRYSTAL17 code running in MPP mode on ARCUS-B,part of the high-performance computing facility at the Universityof Oxford , and on the U.K. national HPC facility ARCHER2.48 The missing metal defect was created by removing a metal atom and replacing two N–Znbonds with N–H bonds similar to the uncoordinated linker. Removinga linker group, in turn, led to the missing linker defect, where thetwo unsaturated metal sites were filled by an associating water andthe conjugate base of the proton-donating group. After geometry optimization,vibrational frequencies at the Γ point were computed, and theBerry phase approach was employed to calculate the IR intensities.61 Subsequently, a simulated spectrum was obtained by fitting the calculatedIR intensities with Lorentzian peak shapes with a fwhm of 10 cm–1. To improve the match with the experimental data,the calculated IR spectra were scaled using distinct scaling factorsfor different spectral ranges, unlike adopting an overall scalingconstant.62 For the range from 600 to 850cm–1, the IR spectrum was scaled with a factor of0.936, while the region between 850 and 1050 cm–1 was scaled by 0.964. Higher wavenumbers were scaled by a factorof 0.958.Theoretical vibrational spectra alongwith elastic constants of ZIF-8 and defective ZIF-8 models were calculatedwith the PBEsol-3c method, a cost-effective 'composite method'developedfor solid-state calculations.63 Thesevalues correspond to the independent elastic stiffness coefficients, Cij.53 The unique coefficients were obtained via deformation of the optimizedstructure, using a three-point formula, in the symmetrically requireddirections of both positive and negative amplitudes. These deformationscorrespond to tensile and compressive strains required to obtain theelastic response. The magnitude of each individual strain deformationis defined as 1%, ensuring that the response is in the purely elasticregion. For visualization of the elastic tensors and calculation ofthe mechanical properties, the Elate,64Elam,65 and Mathematica were calculated using the numerical first derivativeof the analytic cell gradients.thematica software


In addition, the effects of catalyst ink compositions, including ionomer to catalyst ratio (0.1 to 0.3), water to alcohol ratio (1:1 to 3:1), and catalyst weight percentage (10% to 30%), are also studied, and the electrodes’ performance variations are less than 10 mV at 2.0 A cm−2. The results show that the PEMWE electrode has superior compatibility and redundancy, which demonstrates the high flexibility of the electrode and its applicability for large-scale manufacturing.The electrode, as one of the most critical components in a proton exchange membrane water electrolysis (PEMWE) cell for hydrogen production, has a significant impact on cell performance. Electrodes that are fabricated via various techniques may exhibit different morphologies or properties, which might change the kinetics and resistances of the PEMWE. In this study, we have successfully fabricated several electrodes by different techniques, and the effects of electrode coating methods , hot press, and decal transfer processes are comprehensively investigated. The performance differences between various electrodes are due to kinetic or high frequency resistance changes, while the influences are not significant, with the biggest deviation of about 26 mV at 2.0 A cm Sustainable energy systems always include various renewable energy sources, such as wind, solar, hydro, etc., but those renewable energy sources are intermittent within hours, days, or even seasons, which are nonreliable and cannot be directly connected to the current electric grid ,2,3,4. TIn a PEMWE device, one of the main components is the membrane electrode assembly (MEA), which typically consists of catalyst-coated membrane (CCM) and porous transport layers (PTLs) , as showCurrently, the most widely used techniques for electrode fabrication include ultrasonic spray, doctor blade coating, rod coating, slot-die coating, painting or brushing, and other novel methods. However, only a few researchers have studied the effects of electrode fabrication methods. For example, Zhang et al. have investigated the electrodes fabricated via decal transfer and direct deposition for CCMs, and they found that CCMs fabricated with a direct spray deposition method displayed better cell performance compared to CCMs fabricated with a decal transfer method, which is mainly due to greatly reduced ohmic resistances and improved mass transport . They alIt also should be mentioned that when fabricating an electrode, most of the techniques require preparation of catalyst ink, and then a deposition process with or without pre/post-treatment. Thus, the composition of the catalyst ink has a great impact on the electrode morphologies and properties, which may result in different performance. Commonly, catalyst ink is composed of solid catalysts, Nafion ionomer dispersion, and solvent. Nafion ionomer in the dispersion is used as a bifunctional material, which is for conducting protons and binding metal catalyst particles within electrodes. Currently, the most widely used solvent includes water, alcohol, or other surfactants. Therefore, catalyst ink is a kind of complex suspension, and the compositions might have some effects on electrode properties and performance. The effects of catalyst ink compositions on MEA performance in PEMWE devices have not been comprehensively investigated and reported yet. In this work, we have fabricated CCMs by using several typical techniques, including ultrasonic spray, blade coating and rod coating, and investigated the effects of decal transfer and hot press processes. In addition, the catalyst ink with different water to alcohol ratios, ionomer contents, and solid metal catalyst contents were studied comprehensively. Various CCMs were characterized in a PEMWE cell, and the polarization curve and electrochemical impedance spectroscopy (EIS) were measured to analyze the performance and kinetic differences. This work provides a comprehensive understanding of the electrode fabrication methods and ink compositions on PEMWE cell performance and helps the large-scale production of MEA for hydrogen production systems.2 powder from Macklin with 99.9% purity was used as the anode catalyst. DI water (18.2 MΩ cm) was made from Heal Force Water Purification System. The n-propanol (>99.5% nPA from Macklin) and Chemours D520 Nafion dispersion were used for catalyst ink preparations as received. A piece of Nafion 115 membrane (DuPont) was used as the material for CCM fabrication. Carbon paper TGP-H-060 from Toray with approximately 78% porosity and 190 μm thickness was used as both anode and cathode PTLs for all short-term performance tests [Pt on carbon (Pt/C) powder from Tanaka Kikinzoku Kogyo TEC10E50E with 50 wt% Pt was used as the cathode catalyst, and IrOce tests , and fre−2 Pt loading [2 anode, with a 2:1 water to nPA volume ratio that was the same for cathode. Then, the effects of coating methods between ultrasonic spray, rod coating and blade coating  was extracted from the left intercept with the x-axis in the Nyquist plots from EIS data. Three samples of each case were prepared and tested to check the repeatability and obtain the error bars.The cell was tested by using the Gamry instrument (Reference 3000 and 30 K booster). First, the cell was conditioned at 0.1 A cm−2 , water to alcohol ratio (1:1 to 3:1), and catalyst weight percentage (10% to 30%). The ink compositions may have impacts on HFR or kinetics, but we have shown that their effects on PEMWE performance are limited, and we have obtained almost identical performance with anode electrodes made from varied ink compositions. This study clearly demonstrates that the PEMWE electrodes have superior good compatibility or redundancy, which can be fabricated by various techniques with very similar performance and kinetics. This high flexibility makes the PEMWE technology a promising approach for green hydrogen production, easier for large-scale manufacturing of electrodes and its commercialization.


Background: Glioblastoma (GBM), one of the most prevalent brain tumor types, is correlated with an extremely poor prognosis. The extracellular matrix (ECM) genes could activate many crucial pathways that facilitate tumor development. This study aims to provide online models to predict GBM survival by ECM genes.Methods: The associations of ECM genes with the prognosis of GBM were analyzed, and the significant prognosis-related genes were used to develop the ECM index in the CGGA dataset. Furthermore, the ECM index was then validated on three datasets, namely, GSE16011, TCGA-GBM, and GSE83300. The prognosis difference, differentially expressed genes, and potential drugs were obtained. Multiple machine learning methods were selected to construct the model to predict the survival status of GBM patients at 6, 12, 18, 24, 30, and 36 months after diagnosis.Results: Five ECM gene signatures  were recognized to be associated with the prognosis. GBM patients were divided into high– and low–ECM index groups with significantly different overall survival rates in four datasets. High–ECM index patients exhibited a worse prognosis than low–ECM index patients. Four small molecules  that might reduce GBM development were predicted by the Cmap dataset. In the independent dataset (GSE83300), the maximum values of prediction accuracy at 6, 12, 18, 24, 30, and 36 months were 0.878, 0.769, 0.748, 0.720, 0.705, and 0.868, respectively. These machine learning models were provided on a publicly accessible, open-source website (https://ospg.shinyapps.io/OSPG/).Conclusion: In summary, our findings indicated that ECM genes were prognostic indicators for patient survival. This study provided an online server for the prediction of survival curves of GBM patients. Glioblastoma (GBM), grade IV glioma, accounts for around 40–50 percent of brain tumors in America . There iThe extracellular matrix (ECM) is mainly produced by fibroblasts and can be classified into two groups: fibrous proteins (collagen and fibronectin) and glycosaminoglycan  . As a reThis study is aimed at examining the association of ECM genes with GBM survival and providing models to predict survival. A total of five ECM genes were selected using bioinformatics analysis to build an ECM index model. A high ECM index was found to be associated with poorer overall survival. Potential drugs were predicted to reverse the negative prognosis of high–ECM index patients. More importantly, machine learning models were constructed to predict the survival status of 6, 12, 18, 24, 30, and 36 months. A free and user-friendly web server based on these machine learning models was provided in this study.The available transcriptome and clinical data of GBM patients from the Chinese Glioma Genome Atlas (CGGA), Gene Expression Omnibus (GEO), and The Cancer Genome Atlas (TCGA) were used as the datasets for finding prognostic biomarkers and constructing prediction models. The samples, whose histology grade was grade IV or diagnosed with GBM, were downloaded and kept for analysis. There were 237 GBM samples from the CGGA dataset , 150 GBMi = (xi–min(x))/(max(x)—min(x)). Here, zi is the normalized value of the gene expression, xi is the expression value before normalization, min(x) is the minimum value of the gene expression in the dataset, and max(x) is the maximum value of the gene expression in the dataset. After normalization, the gene values range from 0 to 1. We used a univariate Cox regression analysis in CGGA, GSE16011, and TCGA-GBM to examine the links between ECM gene  expression and overall survival (OS). The prognostic ECM genes were defined as the genes with p-value<0.05 in the univariate Cox regression analysis. The prognostic ECM genes were overlapped among the three datasets. Then, CGGA was set as the training dataset, GSE16011 and TCGA-GBM were set as the internal testing dataset, and GSE83300 was set as the independent validation dataset. The LASSO method from the “glmnet” package was adopted in CGGA to select the prognostic genes with a high importance value  at 12, 18, 24, and 36 months.The ECM index was calculated using the following formula: ECM index = The expression values of the selected genes were compared between the GBM and normal brain samples from the GEPIA web server . The GEPThe MCP-counter which is capable of estimating the absolute abundance of eight immune and two stromal cell populations in the tumor samples by the expression data was used in this study . The difp-value<0.05 and log2 fold change>0.5 to filter the statistically significant differentially expressed genes (DEGs) in each dataset. The DEGs were overlapped among the three datasets to obtain the robust DEGs. By using the Connectivity Map (CMap) database, we were able to examine the potential drugs with a close correlation to the diseases. The robust DEGs between the low– and high–ECM index groups were submitted to the Cmap database. The connectivity value from the Cmap represents the ability of the drug to reduce ECM formation, and the optimal connectivity value should be −1.In CGGA, GSE16011, and TCGA-GBM, the differences in the expression levels of protein coding genes between the high–ECM index group samples and low–ECM index group samples for each ECM gene were analyzed using the linear models from the “limma” R package . We defiMachine learning methods were used in the construction of models to predict the survival rates of GBM patients at 6, 12, 18, 24, 30, and 36 months after diagnosis. Four machine learning algorithms, including support vector machine (SVM), random forest (RF), generalized linear models (GLM), and artificial neural network (ANN) from the caret R package were considered. To identify the best parameters for model creation, five-fold cross-validation and grid search were utilized. Data merging was performed on the CGGA, GSE16011, and TCGA-GBM datasets, and the samples were separated into the training dataset (60%) and the testing dataset (40%). GSE83300 was set as the independent validation dataset. After setting the best parameters, the models were trained on the training dataset and evaluated on the testing dataset and an independent validation dataset. The receiver operating characteristic (ROC) curve, a plot of sensitivity versus (1–specificity), was used to estimate the performance of models. We used the R package “shiny” to develop a web-based survival rate calculator and survival curve predictor using these machine learning models.In this study, 47 ECM gene sets containing 1,936 unique ECM-related genes were obtained . Among tp-value<0.05; The LASSO technique was used on these 39 prognostic ECM genes in the CGGA, and the results indicated that AEBP1, F3, FLNC, IGFBP2, and LDHA were the best combination of genes to construct the model . A multip-value<0.05; p-value<0.05; In CGGA, GSE16011, and TCGA-GBM, the GBM patients were classified into two groups by the median gene expression of the five selected genes . Then, survival analysis was used to assess the relationship between the gene expression value and OS. There were significant negative correlations between the expression levels of AEBP1, F3, FLNC, and LDHA in CGGA , and GBM. The results from the GEPIA dataset showed that the expression values of these genes were higher in the GBM samples than in the normal brain samples , which contains 50 GBM patients, was used to validate the results. The ECM index distribution, overall survival, and ECM gene expression profiles in GSE83300 are plotted in We calculated the association between the ECM index and population abundances of the immune and stromal cells in the combined CGGA, GSE16011, and TCGA-GBM datasets. As shown in Data profiles from CGGA, GSE16011, and TCGA-GBM were used to find the DEGs between the high– and low–ECM index groups. DEGs calculated from the three datasets were overlapped to obtain the robust DEGs, and a total of 286 robust DEGs were identified. To predict the potential drugs for GBM, CMap was implemented on the robust DEGs between the low– and high–ECM index groups. The 20 drugs with high and significant associations with robust DEGs are listed in via a five-fold cross-validation strategy, we calculated the AUC value in the testing dataset to characterize the ability of the model to distinguish between the dead and alive. KNN, RF, ANN, ANN, RF, and RF demonstrated the highest AUC values in predicting the survival status at 6, 12, 18, 24, 30, and 36 months  and testing (40%) datasets. The commonly used machine learning classifiers, including GLM, ANN, SVM, KNN, and RF, were constructed to predict the survival status of patients at 6, 12, 18, 24, 30, and 36 months after the treatment, respectively. After setting the best parameter 6 months , F, resp6 months , respecthttps://ospg.shinyapps.io/OSPG/;(2) inputting the values of five genes, including AEBP1, F3, FLNC, IGFBP2, and LDHA ; 3) inputting the values of age and gender ; 4) selecting the machine learning models for each time point , and 5) clicking the “submit” button. An example is illustrated in To make these constructed machine learning models accessible to GBM researchers, we developed a web tool to predict the survival probability of GBM patients called OSPG. OSPG can be used in five steps 1) visiting the website The prognosis of GBM is very poor; only about 5 percent GBM patients could survive more than 5 years . CurrentECM is one of the major components of the TME, and its interaction with the tumor cells promotes tumor growth and migration . Thus, cAEBP1 has the potential to bind with collagen and then contribute to collagen polymerization, which is critical for several biological processes such as tissue repair and fibrosis . The higRecently, a systematic review summarized the available models for the survival prediction of GBM . It is aThe advantages of this study were that it provided accurate models and constructed the web server. In the independent dataset, the machine learning models reached the AUC values of 0.878 and 0.868 in predicting the survival status at 6 and 36 months , respectNevertheless, the present study has several limitations. First, although validation datasets were used in this study, the models need to be carefully assessed and validated by future prospective studies. For example, the survival status of GBM patients could be predicted by the machine learning models and expression profiles of these five genes. Then, the accuracy of our models could be validated by comparing the predicted and real survival status. Second, the roles of the selected genes in GBM also need to be tested by experiments.We identified the ECM genes with prognostic power and offered potential small-molecule drugs for the treatment of GBM. The online web server based on the five ECM genes could accurately predict the survival curves of GBM patients after the diagnosis, which could be particularly useful for tailoring clinical care to the needs of the individual GBM patient.


GST, AT, UFGT and SPS, HT, PK gene expressions. These results suggest that potassium deficiency inhibits anthocyanin and sugar metabolism. In addition, it promotes the up-regulation of KUP expression, which is the main cause of K accumulation in fruits. Together, our data revealed the molecular mechanism in response to different K levels during fruit quality formation and provides the scientific foundation for the improvement of fruit quality by adding K fertilizer.Inadequate potassium (K) availability is a common abiotic stress that limits the growth and quality of fruit trees. Few studies have investigated the physiological and molecular responses of grapes at different potassium levels. In this study, an integrated approach was developed for grapevines grown at four different potassium fertilization levels  in combination with metabolite measurements and transcript analysis. The results showed that different K levels affected the accumulation of sugars and anthocyanins in the fruit. At 78 days after bloom (DAB), the K150, K300, and K450 treatments increased soluble sugar content by 37.39%, 31.10% and 32.59%, respectively, and anthocyanin content by 49.78%, 24.10%, and 13.06%, respectively, compared to K0. Weighted gene co-expression network analysis (WGCNA) of DEGs identified a network of 11 grapevines involved. During fruit development, potassium application promoted the accumulation of anthocyanins and sugars in fruit by regulating the up-regulation of  Vitis vinifera L.) is extremely important to the economies of all countries as a fruit, consumed worldwide as fresh fruit, raisins, and wine . In the randomized block experiment, every three trees were a treatment, and each treatment was repeated three times; three trees were spaced between treatments as protection plants. Potassium sulfate was applied at 50 DAB. Samples were collected from 50 DAB and every 7 days until maturity, and a total of 5 samples were collected. During the sampling process, 50 berries were randomly removed from different locations in different bunches of several vines in each treatment, replicated three times, and brought back to the laboratory in ice boxes. Each treatment was brought back to the laboratory for the determination of physiological indicators, such as soluble solids content, soluble sugar, and titratable acid content. Samples were frozen in liquid nitrogen and kept in the refrigerator at −80 °C until used for RNA-Seq.3, AR, 98%), which were digested and analyzed with ICP-AES ICP6300 .Concentration of K was determined by Liang B et al. . In brieL*, a*, b*, and color space units. L* is the luminance , a* is the red/green value , and b* is the yellow/blue value .The color was assessed by a CM-2600d colorimeter , using the CIElab color system. Two equidistant color measurements were performed near the equator of each fruit using A digital refractometer  was used to measure the soluble solids (SSC), and titratable acid (TA) was measured by using a previously reported acid-base titration . Determiv/v) at 1 ml·min−1.The concentration of glucose and fructose was measured in accordance with the method of Liu et al. . In shor−1 metaphosphate solution at column temperature 25 °C, flow rate 0.5 ml·min−1; the injection volume is 5μl, and the detection wavelength is 214 nm.The extraction and determination of organic acids were carried out in accordance with Zhang et al. . An amouThe pulp and peel of each treated grape were mixed and immediately placed in liquid nitrogen; each sample was 3 biological replicates, and the sample RNA extraction and transcriptome sequencing were entrusted to ‘Beijing Nuohe Zhiyuan Technology Co., Ltd.’ in Beijing, China. Total RNA was extracted using the RNA prep Pure polysaccharide polyphenol plant total RNA , and the cDNA was reverse-transcribed with the M5 Super plus RT-qPCR kit with the gDNA remover kit . All steps were performed according to the reagent instructions. The cDNA library was obtained by reverse transcription and PCR amplification after RNA detection, and after the library inspection was qualified, it was sequenced on the Illumina platform. After obtaining raw data (raw reads) by sequencing, the original data of the sample was processed to obtain high quality data on quality (clean data), and the sequence comparison with the reference genome was used to obtain data for subsequent analysis.p-value < 0.05 as the screening criteria, screening for differentially expressed genes between samples. DEGs were combined with GO (Gene Ontology), and the KEGG  and |log2fold changes|≥1, and a corrected In order to simplify the genes into co-expression modules, a weighted gene co-expression network analysis (WGCNA) was performed using default settings in R . The FPKhttps://www.ncbi.nlm.nih.gov/tools/primer-blast (accessed on 14 December 2022)) using VvGAPDH as the reference gene  method (2−△△CT) [Based on the enrichment results and WGCNA analysis, the different expression of genes involved in the metabolic pathways were screened, for example, ion transport and anthocyanin biosynthesis, and 11 key genes were selected for RT-qPCR verification and analysis; all 11 candidate genes were upregulated relative to the K0 treatment group. Primers were designed using Primer BLAST .The potassium content of fruit was on the rise during the whole development period, and the effect of potassium treatments at different concentrations on potassium accumulation in fruit was different. Compared with the K0, the concentrations of K150, K300, and K450 increased the potassium content by 11.38%, 15.40%, and 8.37% at 78 DAB, respectively .The potassium content of the soil under different treatments was different at 78 DAB. The lower potassium content was, the more potassium was transferred to the aboveground part; the higher potassium content was, the less potassium was transferred to the aboveground part. Therefore, it can be explained that the potassium transferred to the aboveground section under the three treatments  was higher than K0. In addition, the K150 treatment effect was the best .The accumulation of anthocyanins is not only related to the color of the fruit skin, but is also an important indicator of fruit ripeness. The anthocyanin content and SSC under the four treatments showed an upward trend in general. Compared with the K0, the concentrations of K150, K300, and K450 increased the anthocyanin content by 49.78%, 24.10%, and 13.06%, respectively, A and theThe content of soluble sugars in the fruit was closely related to the quality and ripeness of the fruit. At 57 DAB, the soluble sugar content of fruit was increased, and it increased rapidly at 71–78 DAB. At 78 DAB, the soluble sugar content of K150 treatment was the highest. Compared with the K0, the concentrations of K150, K300, and K450 increased the soluble sugar content by 37.39%, 31,10%, and 32.59%, respectively A.At 78 DAB, the fruit under K150 and K300 treatments had the lowest TA content. At 50 DAB, the TA content between each treatment was not significant. At 78 DAB, compared with the K0, the concentrations of K150, K300, and K450 decreased the TA content by 22.06%, 21.84%, and 15.98%, respectively B.Different concentrations of K treatments have a significant impact on the content of glucose, fructose, tartaric acid, and malic acid in the fruits, which can play a role in increasing sugar and reducing acid. The content of glucose and fructose was increased by potassium fertilizer treatments at different concentrations. As the fruit developed, the concentration of sugar components in the fruit gradually increased. Compared with K0, the concentrations of K150, K300, and K450 increased the glucose content by 25.51%, 34.50%, and 19.12%, respectively, A and theThe content of malic acid and tartaric acid in different K treatments was lower than K0. Compared with K0, the concentrations of K150, K300, and K450 decreased the tartaric acid content by 11.15%, 24.84%, and 29.53%, respectively, A and theL*, a*, b* and CIRG color indices are highly correlated with the color of grape berry, and they have been successfully applied to indicate the color of berry. In general, different concentrations of potassium treatments have an impact on the color of grape fruit: L* value represents brightness—the larger the L* value, the brighter the color, the smaller the L* value, the darker the color, the closer to purple-black; the higher the a* value, the higher the red component of the fruit, that is, the more deviation from the purple-black; the b* value represents the yellow-blue difference index—the larger the positive value, the darker the yellow, the smaller the negative value, the deeper the blue. The test shows that the K150 and K300 treatment color is closer to purple-black  from four treatments was carried out on the Illumina platform, and the Clean Data of each sample reached more than 6.30 Gb. The Q20 and Q30 sequences accounted for more than 95% (the sequencing error rate <1%), and more than 90%, respectively, and the GC content was greater than 45% . PairwisTo analyze the function of genes’ different expressions in response to K at 78DAB, the DEGs were enriched with Gene Ontology (GO). The top 20 GO enrichment entries for abundance are shown . In the Co-expression networks were constructed using 31,740 DEGs in WGCNA A. FPKM vAT), glutathione-S-transferase (GST), UDP-glucuronosyltransferase (UFGT), and potassium transporter (KUP). Three genes from the blue module and one gene from the yellow module  correlated with sugar and potassium transporters were identified as Sucrose-phosphate synthase (SPS), Pyruvate kinase (PK), and potassium transporter (KUP). These alleged main candidates are highlighted in red in the gene pool and selected based on their importance in the module  and their expression profiles. The 11 major candidate genes predicted from the turquoise, blue, and yellow modules and the annotations are listed in To further explore candidate genes that contribute significantly to the gene network, annotation information for all selected genes was obtained from the Grapevine Reference Genome Annotation Database C–E. ThisUFGT, GST, AT, SPS, PK, HT, and KUP genes promoted the accumulation of anthocyanins, sugars, and potassium in fruits at 64 and 78 DAB. K150 and K300 had significant effects on genes related to potassium transporter, sugar accumulation, and anthocyanin synthesis at 78 DAB.RT-qPCR analysis of 11 differential genes was performed . During GST, AT, and three UFGT genes, were upregulated upon K treatment. Among them, the expression of UFGT is essential for anthocyanin biosynthesis [GST is involved in anthocyanin transport. UFGT is involved in glycosylation transfer, which transfers UDP-glucose to the C3 hydroxyl group of anthocyanins, producing anthocyanin 3-glucoside, which improves the color of flowers or fruits. Anthocyanin acyltransferases modify the unstable anthocyanins [Flavonoids, especially anthocyanins, are the main pigments that determine the color of the grape fruit. As previously mentioned, anthocyanin accumulation was rapidly induced by K application . Transcrynthesis . In the ynthesis . All fivocyanins . These rIt is well known that K is essential for the activity of many enzymes in plants . TranscrSPS, PK, HT) were detected in this study. SPS, Sucrose phosphate synthase, is the rate-limiting enzyme in sucrose synthesis, and PK, Pyruvate kinase, is the rate-limiting enzyme in glycolysis and regulates C/N metabolism in metabolic enzymes [HT) genes also respond to K treatment. In general, compared with the K0 at 78 DAB, the sugar-related genes at different K levels were relatively up-regulated, increasing the concentration of glucose and fructose in grape fruits. This is in line with previous research findings [In this study, the expression of some genes related to sugar metabolism were influenced by K treatment. Three sugar-related genes  was significantly increased. In contrast to that study, our study focused mainly on grape fruit. This study found that the levels of gene expression and channels of K transporters significantly up-regulated the K treatment compared with K0 , sugar metabolism genes , and anthocyanin genes , thus improving fruit quality. However, low potassium is better than high potassium. This is the first comprehensive study using transcriptomics to study the response of grape berries to low and high potassium environments. The results of this study will provide a theoretical basis for further research on the regulatory mechanism of some candidate genes, reveal the molecular mechanism of improving fruit quality through potassium addition, and also provide a scientific basis for the rational application of potassium fertilizer by fruit farmers in production; of course, some functional validation is necessary in subsequent studies, which are essential to further elucidate the mechanism of fruit growth in grapes due to K/deficiency conditions of application.The results showed that K content, sugar concentration, and anthocyanin content in grapes were significantly affected by K levels, especially when treated with K150 and K300. We performed RNA-Seq on fruit samples collected from 50, 64, and 78 DAB and analyzed gene expression related to sugar, anthocyanin, and potassium concentrations to determine the molecular mechanisms explaining the different responses of fruit to low and high potassium. Based on the analysis of biological functions, the majority of differentially expressed genes were found in the ‘metabolic pathway’, ‘hormonal signal transmission’, ‘ion transmembrane transport’, and ‘ROS reaction’. Different levels of potassium treatment can promote the accumulation of potassium, sugar, and anthocyanin by inducing the up-regulation of potassium transporters genes (3