Omsk haemorrhagic fever virus (OHFV) is the agent leading to Omsk haemorrhagic fever (OHF), a viral disease currently only known in Western Siberia in Russia. The symptoms include fever, headache, nausea, muscle pain, cough and haemorrhages. The transmission cycle of OHFV is complex. Tick bites or contact with infected small mammals are the main source of infection. The Republic of Kazakhstan is adjacent to the endemic areas of OHFV in Russia and febrile diseases with haemorrhages occur throughout the country—often with unclear aetiology. In this study, we examined human cerebrospinal fluid samples of patients with suspected meningitis or meningoencephalitis with unknown origins for the presence of OHFV RNA. Further, reservoir hosts such as rodents and ticks from four Kazakhstan regions were screened for OHFV RNA to clarify if this virus could be the causative agent for many undiagnosed cases of febrile diseases in humans in Kazakhstan. Out of 130 cerebrospinal fluid samples, two patients (1.53%) originating from Almaty city were positive for OHFV RNA. Screening of tick samples revealed positive pools from different areas in the Akmola region. Of the caught rodents, 1.1% out of 621 were positive for OHFV at four trapping areas from the West Kazakhstan region. In this paper, we present a broad investigation of the spread of OHFV in Kazakhstan in human cerebrospinal fluid samples, rodents and ticks. Our study shows for the first time that OHFV can not only be found in the area of Western Siberia in Russia, but can also be detected up to 1.600 km away in the Almaty region in patients and natural foci. Omsk haemorrhagic fever virus (OHFV), a positive-sensed, single-stranded RNA virus. The virus may infect humans as a dead-end host and can lead to a biphasic course [Omsk haemorrhagic fever (OHF) is a zoonotic infectious disease presently only reported in regions of the Russian oblasts (=regions) Kurgan, Tyumen, Omsk and Novosibirsk in Siberia ,2,3. Thec course . A seconc course . The casc course , but duec course , many inThe first epidemic outbreak occurred in Russia between 1945 and 1958, with 972 confirmed cases and over 1500 suspected cases of OHF. Until 1998, more than 300 OHF cases were confirmed in the regions Tyumen, Kurgan, Omsk and Novosibirsk. Between 1970 and 1975, a study with 577 patients with fever of unknown origin (FUO) showed exposure to OHFV in 18%. The results showed that persons with the mean age of 20–40 years were mainly affected, regardless of sex, as well as 30% of children up to 15 years. Muskrat trappers, poachers and their family members are one of the major risk groups ,11. No fFlaviviridae [Alkhurma haemorrhagic fever virus, Gadgets Gully virus, Kyasanur Forest disease virus (KDFV), Tick-borne encephalitis virus (TBEV), Langat virus, Louping ill virus (LIV), Powassan virus (POWV) and the Royal Farm virus [OHFV belongs to the tick-borne encephalitis (TBE) complex of flaviviruses in the family of iviridae . Other mrm virus ,15,16,17rm virus . Interesrm virus ,8,13. Inrm virus ,18,19. Orm virus . The ORFThe 5′ UTR has a length of 123 nt and contains a secondary structure in a conserved region of a stem loop and an additional stem loop at the 5′ end. However, this additional stem loop was shown to be 29 nt different from other representatives of the TBE complex . The 413Bogoluvovska (NC_005062) and the Kubrin strain are the same, due to a mix-up of samples in the laboratory [There are contrary opinions on the different subtypes of OHFV and the resulting phylogeny. Currently, there is a discussion on whether two or three subtypes can be distinguished. Early studies from the 1970s suggest that OHFV can be distributed into a minimum of three subtypes , which iFlaviviridae. It is transmitted to humans by tick bite or via direct contact with infected animals, through respiratory or nutritive pathways. No person-to-person transmission has been reported so far [Dermacentor reticulatus  is trginatus ,28. Bothushrooms . Further of OHFV . Additio of OHFV .Ondathra zibethicus) [OHFV can also be detected in and transmitted by mammals such as the muskrat (ethicus) . The musethicus) . The excethicus) . Naturalethicus) ,29.Currently, OHF infections and its agent OFHV are only reported and known in the Russian Federation ,2. Thus 2—most people, however, are urban citizens [The Republic of Kazakhstan is located in Central Asia and is adjacent to Russian Western Siberia. It borders China in the east, Turkmenistan in the south and Uzbekistan, Kyrgyzstan, Russia as well as the Caspian Sea in the west. The climate in Kazakhstan has a continental character. Kazakhstan itself is divided into 14 regions with three major cities. It has approximately 19 million inhabitants, with a theoretical population density of seven inhabitants per kmcitizens . In Kazakhstan, there are many cases of fever with unknown origin and many endemic viruses lead to diseases that have similar, non-specific symptoms ,34,35. IWe suggest that, due to the close geographic proximity to OHFV-endemic regions in Russia, OHFV might also be present in Kazakhstan. Hence, it should be possible to also detect OHFV in humans as well as reservoir hosts such as rodents and ticks in Kazakhstan. Here, we are conducting for the first time a broad investigation on the spread of OHFV in Kazakhstan by screening patient-derived cerebrospinal fluid samples (CFS) from Almaty, Akmola and East Kazakhstan and hosts such as ticks from North Kazakhstan, Akmola and Almaty and small rodents from the Almaty and West Kazakhstan regions. With these widespread areas, we are able to cover regions that are different in climate and in geographic and potential habitats, to gain more insight into the ecology and complexity of the transmission cycle of OHFV in Kazakhstan.In the years 2018 and 2019, serous meningitis patients with symptoms such as headache and/or meningeal signs were recruited for a cross-sectional study in the Republic of Kazakhstan in eight hospitals in the regions of East Kazakhstan, Akmola and in Almaty city . After sEach specimen was paired with a detailed, anonymised list of clinical symptoms such as meningitis, encephalitis, headache and/or nausea, vomiting and unconsciousness, as well as a questionnaire with questions regarding sociodemographic factors .Ticks were collected in three Regions of Kazakhstan  at eleven sampling regions, with, in total, 26 different sampling sites during the peak season of tick activity in May and June. In 2016 , 2018 aThe Almaty region was examined in five sampling areas  and Almaty city itself at seven sampling sites . ticks = 4993 male and female adults), they were pooled in vials of 1–5 ticks (npool = 1058) and stored at −20 °C until further analysis.All ticks were collected by flagging with white cotton sheets and stored in tubes at −20 °C corresponding to the sampling area. Later, ticks were morphologically identified following the official guidelines for tick identification in Kazakhstan ,39,40. AIn West Kazakhstan , in the Almaty region  and in Almaty city, small rodents were trapped with snap traps and pork-fat-covered bread as bait during all seasons of 2018 and 2019 . Captureg. RNA was isolated from 140 µL of the supernatant using a commercial kit , according to the manufacturer’s manual, and stored in aliquots at −80 °C [Tick pools, rodent lungs and brain tissues were homogenised with two stainless steel beads and 1 mL of cell culture medium  using the TissueLyser II (2 min at 30 Hz) . The homogenised samples were centrifuged for 5 min at 2348× t −80 °C .Bogolubovka and other members of the TBE complex, such as Langat virus, TBEV Far Eastern subtype Sofjin and LIV. It was also tested against other flaviviruses, such as Dengue virus (type 1–4), Zika virus, Yellow-fever virus, West-Nile virus (WNV), Bagaza virus, Dakar bat virus, Kedougou virus, Spondweni virus and Usutu virus, as well as other agents with the potential to cause Encephalitis, such as Western Equine Encephalitis virus, Eastern Equine Encephalitis virus, Varicella Zoster virus and Herpes Simplex virus (type 1 and 2) -PCR was used to screen human liquor, tick, rodent lung and rodent brain tissue samples. Primers OHF-d1F (5′-GGCACARACCGTTGTTCTTGAGCT-′3) and OHF-d2R (5′-GCGTTCWGCATTGTTCCAWCCCACCAT-′3) and a TaqMan probe (5′-JOE-AGGTGTTCTGCTGTCTTGTCGAGCACCT-BQH1-′3) were used, detecting a conserved region within the envelope gene of OHFV RNA [1 and 2) .www.mapchart.net (accessed on 16. January 2022).To calculate the prevalence of OHFV in the regions, the Minimum Infection Rate (MIR) method was applied, since the investigated flavivirus only shows a low prevalence (lower than 5%) in the investigated areas . MIR is Langat virus and the TBEV Far Eastern subtype strain Sofjnn. Further, we screened for more remotely related flaviviruses including Dengue virus (type 1–4), Zika virus, Yellow-fever virus and WNV (Bogolubovka) specimen showed an expected strong signal. Hence, the used real-time RT-PCR assay is highly sensitive and can be exclusively be used for the detection of OHFV.In this study, we aimed to identify OHFV, a member of the TBE complex virus family in CFS, in ticks and rodent tissue in the Republic of Kazakhstan. OHFV has a lot of sequence similarity to other closely related flaviviruses. To ensure the specificity of the published primers OHF-d1F and OHF-d2R, and the TaqMan probe targeting the E-gene of OHFV [ and WNV . The priThis establishment of a reliable diagnostic allows for the systematic screening of the existence of OHFV in Kazakhstan. As a proof of principle, we first concentrated on the analysis of a collection of human CFS specimens from patients with symptoms such as headache and meningism , being, Two out of the 130 CSF specimens tested positive for OHFV RNA (1.53%). Both patients were treated in the Almaty City Hospital . All 128The first patient was a 33-year-old male, born and living in Almaty city in a rental flat. He stated that he had no contact with any animals such as sheep, cattle, dogs or cats. Furthermore, he did not remember any tick bites. The clinical symptoms that he reported on the day of hospitalisation were headache and neck pain. His temperature, blood pressure and pulse rate were in a normal range. The second patient was a 22-year-old female, born in the Kyzylorda region, but now living in Almaty city in a city apartment. She had recently visited Kyzylorda but also did not remember any contact with animals or any tick bites. She was hospitalised with fever (>37.5 °C) and headache. The blood pressure was in normal boundaries but the pulse rate was increased (<80). Dermacentor marginatus , D. reticulatus , D. niveus  and Ixodes persulcatus . In the Sandyktau area , MIR of D. marginatus at village Sandyktau, Akmola region, in 2016: 0.01) and five positive pools of D. reticulatus originating from flagging in 2018 (5 out of 39 pools (12.8%), MIR of D. reticulatus at village Sandyktau, Akmola region, in 2018: 0.17). Furthermore, there were two OHFV RNA-positive pools from the Sadovoye area from 2018 , MIR of D. marginatus 0.02; MIR of I. persulcatus 0.5, both at village Sadovoye in Akmola, 2018). In total, of 21 investigated I. persulcatus tick pools, one in Akmola from the Sandyktau area at the village Sadovoye was positive for OHFV  , divided into 1058 pools, were investigated from three regions  . All posApodemus uralensis (n = 259), Mus musculus (n = 128) and Rattus norvegicus (n = 39), the family Gerbilinae represented by Meriones meridianus (n = 2), the family Cricetidae represented by Microtus arvalis (n = 86), Microtus kirgisorum (n = 49) and Clethrionoyms glareolus (n = 12) and the family Gliridae represented by Dryomys nitedula (n = 15). Additionally, insectivores such as Crocidura suaveolens (n = 28), Soricidae (Sorex araneus (n = 1), Sorex minutus (n = 1) and a not further classified Sorex spp. (n = 1)) were trapped and lung and brain tissue samples were screened for OHFV  , in one specimen of A. uralensis from Oral City , as well as from one specimen of A. uralensis from the Bayterek District   . Further8, 1.7%) . All posAll other lung tissue samples, as well as all brain tissue samples from small mammals originating from the West Kazakhstan region (2019), Almaty region and Almaty city from 2018 and 2019, were negative for OHFV RNA., Crimean-Congo haemorrhagic fever virus (CCHFV) [Rickettsia spp. [Orthohantavirus and Rickettsia spp. (data not shown). Although it was shown that the selected diagnostic primers identified OHFV with high reliability , there r (CCHFV)  and Ricksia spp. . All posIn conclusion, OHFV was, for the first time, detected in human patients, ticks and rodents outside of Russia in the Republic of Kazakhstan.D. reticulatus, which was also the tick mainly collected in the regions of North Kazakhstan and Akmola ((O. zibethicus), the most well-known spreader of OHFV, have been reported along the rivers of Kazakhstan [OHFV is currently only known to be prevalent in four regions of Russia, namely Kurgan, Tyumen, Omsk and Novosibirsk. Only in these regions, irregular but frequently recurring outbreaks of OHF among the population are recorded ,2,3,7. Td Akmola . Furtherzakhstan . Since aFor this reason, we examined areas of Kazakhstan that are adjacent to the Russian OHFV epidemic areas, such as North Kazakhstan and the Akmola region. In order to establish a cross-sectional study, it was supported by also examining more remote regions such as West Kazakhstan in the west and East Kazakhstan and the Almaty region in the south east of Kazakhstan. Arthropod-borne viral diseases usually have a natural cycle that includes ticks and small rodents as natural reservoirs. The human is usually a dead-end host. In order to draw a complete picture of the distribution of OHFV in Kazakhstan, we screened CSF from human patients with meningitis, pools of ticks and captured small rodents. The screening on CSF was based on a collection of 130 samples from a previous study about serous meningitis patients of unknown aetiology . HoweverDermacentor that were positive for OHFV, confirming its important role in the spread of OHFV. Furthermore, we also detected positive pools of I. persulcatus. As already discussed elsewhere, Ixodes seems to play a potential role in the sylvatic life cycle of the agent [Nevertheless, in other areas, ticks and rodents were indeed positive for OHFV. We identified ticks of the family he agent ,29.D. marginatus and D. reticulatus and also I. persulcatus) were collected in forest steppe areas with many lakes and rivers. In contrast to this, all tick and rodent sampling sites in the region of North Kazakhstan were quite distant from the next river. One could postulate that the spread of OHFV follows the tracks of waterways, since the muskrat has populated rivers in Central Asia since its release there in the 1930s [Arvicola amphibius [Microtus spp. [Surprisingly, rodents from West Kazakhstan, a region far away from the known OHFV-endemic regions in Siberia, tested positive for OHFV. It was interesting, however, that all positive rodents were collected in areas close to lakes and rivers. The infected rodents of West Kazakhstan, for example, were collected in the village of Teretiki and around the city of Oral, which is close to the river Ural. Additionally, in Akmola, the positive ticks  , contrar% , contrTo complete this interesting evidence of an OHFV distribution in Kazakhstan, the positive samples need to be sequenced. It is also not possible to say into which OHFV subtype according to Kovalev et al., 2021 [Therefore, it is important to start a systematic cross-sectional and longitudinal study in Kazakhstan including more data of OHFV in patients, rodents and ticks to clarify open questions and to gain a complete picture of OHFV in Kazakhstan—a virus that now officially has left Russian territory and spreads over Central Asia. Future studies will give a deeper insight into the emergence and spreading mechanisms of OHFV all over Kazakhstan.


Despite the extraordinary and exceptional advances in drugs and vaccine development, sophisticated diagnostic facilities in health care settings, strategies in disease prevention and control, emerging and re-emerging infections are still the leading cause of death and suffering amongst human and animal populations with great impact on the world economy. Monkeypox is a viral disease with the potential to spread across the globe through international travel and movements of animals from endemic areas to susceptible populations. Monkeypox virus is an uncommon but endemic viral disease in Africa, but recent outbreaks occurred in Europe, the US, UK, Spain, Portugal, Sweden, and Italy. There is a need to refurbish the healthcare settings and get prepared for future outbreaks, especially in developing countries with poor healthcare delivery services. Scientists and researchers should also focus on developing vaccines, treatment, and preventive measures before the virus spread further. In May 2022, a cluster of pox-like diseases surfaced Europe, including United State and the United Kingdom. Following laboratory diagnosis, it was confirmed Monkeypox virus disease. Monkeypox is a DNA virus, a member of the genus Orthopoxvirus of the family Poxviridae . The firHowever, the recent outbreak of Monkeypox virus according to World Health Organization, the first index case of Monkeypox in the United Kingdom was identified on 7th May 2020 from an individual with a travel history to Nigeria, however, a week later 2 new cases were confirmed from Individuals of the same family having no connection with the first case. Four new cases were further identified that also do not have any link with previous cases or any travel history but were men who were identified to have sex with men, and the source of infection is not confirmed.Therefore, the virus is circulating within the population. Monkeypox is of public health importance due to its morbidity and mortality rate and its economic significance.This article is aimed at discussing the current effort in controlling and preventing the spread of Monkeypox and the challenges facing its responses in the United Kingdom.Monkeypox virus is an endemic disease in West and Central Africa. However, following its first-ever diagnosis in the Democratic Republic of Congo, precisely in the year 1970, the cases escalate where they appear in many African and European countries. Studies conducted show that the increase in Monkeypox cases among the human population may be attributed to the stoppage of vaccination against smallpox that usually renders a cross-protection against Monkeypox . HoweverThe clinical signs of Monkeypox virus manifest 5–21 days (three weeks) following infection, initially it is characterized by severe fever, headache, lymphadenopathy, and muscles pain which is followed by rashes all over the body that appear on different levels from macules, papules, vesicles and pustules .Monkeypox virus is a zoonotic disease. Therefore, to prevent the occurrence of this infection there's a need for a multidisciplinary approach . Monkeypox virus can be prevented by strict hygiene and sanitation, proper meat inspection, limiting access to hunting wild animals, consumption of bush meat should be avoided at all costs, and proper storage of foodstuffs in households to prevent contamination by rodents.The spread of the Monkeypox virus can be controlled by the administration of a vaccinia immune globulin .Monkeypox virus infection has no available treatment, however, several antiviral s drugs were employed to treat the infection locally and systemically. The antiviral drugs include Cidofovir, Tecovirimat, and Brincidofovir .The UK health authorities have established a rapid response team with the mandate of coordinating extensive contact tracing in health care settings and the wider community, that is tracing individuals who encounter infected or confirmed cases.Moreover, the assessment of individuals that encounters the confirmed cases, is also followed by surveillance for 21 days. Administration of vaccines to individuals with a higher risk of contact. Furthermore, an investigation is also ongoing to determine the route of acquisition that would help in determining other routes of transmission within the population.The major challenge is that the main source of infection is not identified, which is the major determinant in breaking the chain of disease transmission in a population.Furthermore, the extent of local transmission is ill-defined, therefore more cases could be identified, or a certain number of individuals may be infected without showing clinical signs of the disease. There would be a low level of herd immunity, as the infection is not endemic in the United Kingdom.It is very essential to increase surveillance of the virus in health care settings and within the community, especially in animal populations such as farms, animals, markets, and abattoirs.People coming from other countries where the disease is endemic should be screened and confirmed free of infection before coming in. Infected individuals should be monitored to prevent the further spread of the virus to susceptible individuals. People should be educated and enlightened on the dangers of bushmeat consumption, zoonosis, the importance of one health, and most importantly implementation of preventive measures and biosecurity against the Monkeypox virus. Finally educating health workers on how to prevent themselves, because they are at higher risk of being infected.All the authors declare no conflicts of interest.


We propose the use of reduced order modeling (ROM) to reduce the computational cost and improve the convergence rate of nonlinear solvers of full order models (FOM) for solving partial differential equations. In this study, a novel ROM-assisted approach is developed to improve the computational efficiency of FOM nonlinear solvers by using ROM’s prediction as an initial guess. We hypothesize that the nonlinear solver will take fewer steps to the converged solutions with an initial guess that is closer to the real solutions. To evaluate our approach, four physical problems with varying degrees of nonlinearity in flow and mechanics have been tested: Richards’ equation of water flow in heterogeneous porous media, a contact problem in a hyperelastic material, two-phase flow in layered porous media, and fracture propagation in a homogeneous material. Overall, our approach maintains the FOM’s accuracy while speeding up nonlinear solver by 18–73% (through suitable ROM-assisted FOMs). More importantly, the proximity of ROM’s prediction to the solution space leads to the improved convergence of FOMs that would have otherwise diverged with default initial guesses. We demonstrate that the ROM’s accuracy can impact the computational efficiency with more accurate ROM solutions, resulting in a better cost reduction. We also illustrate that this approach could be used in many FOM discretizations . Since our ROMs are data-driven and non-intrusive, the proposed procedure can easily lend itself to any nonlinear physics-based problem. The PDEs can be solved analytically for simple geometries and boundary conditions. For complex problems with non-homogeneous boundary and initial conditions, various geometries, and/or material properties, however, numerical approximations such as finite difference, finite volume, or finite element methods, referred to as full order model (FOM) hereafter, are primarily used to solve these governing equations7. Although the FOMs have been widely used, they require substantial computational resources, making them not practically suitable for handling large-scale inverse problems, optimization, or control, in which an extensive set of simulations must be explored10. Besides, as PDEs become nonlinear, the solver used to approximate usually takes considerable time to converge or, in the worst case, does not converge at all.Many natural and engineering processes ranging from subsurface flow and mechanical physics, aerospace engineering to material science are governed by partial differential equations (PDEs)11. In this work, ROM is suitable for a parameterized problem, where the problem is repeatedly evaluated with a set of parameters 12. ROM is generally composed of two stages, the offline and online stages. The offline stage begins with the initialization of the set of 13 that span a reduced space of very low dimensionality but with enough accuracy for a reproduction of the FOM15. During the online or prediction phase, ROM can deliver an approximation of FOM for any desired value of Reduced order modeling (ROM) is emerging as an alternative that provides a reasonable accuracy while requiring a much lower computational cost compared to the FOM16 and generalized eigenvalue problems17. The reconstruction of FOM from linear reduced manifolds is completed through either Galerkin or Petrov-Galerkin projection19. This approach has the primary advantage of preserving physical laws and requiring less training data. The non-intrusive (data-driven) ROM, on the other hand, can straightforwardly utilize both linear and nonlinear reduced manifolds constructed by POD or an autoencoder26 interchangeably because of no modification to the ROM solution algorithm. The reconstruction operation also bypasses an expensive Galerkin or Petrov-Galerkin projection by using any regression model such as Gaussian process, radial basis function regression, or artificial neural networks to map between There are generally two types of ROM; intrusive and non-intrusive ROM. An intrusive ROM often relies on proper orthogonal decomposition (POD) as a linear compression tool. However, nonlinear manifolds have recently been incorporated into intrusive ROMs  for PDEs28 and can be applied to any physics-based problems easily. Additionally, the non-intrusive ROM proposed by Kadeethum et al.30 illustrates its capacity to handle high-dimensional input, which is extremely difficult for POD-based ROM due to its dependence on a high dimensional reduced basis 29. Another advantage of non-intrusive ROMs for coupled multiphysics processes  is to selectively focus on the quantities of interest31. For instance, if we are interested in the saturation field of the two-phase flow problems, we can build our non-intrusive ROM for the saturation field without necessarily constructing the ROM for pressure and velocity fields, which could save substantial computational resources.This study utilizes a non-intrusive ROM approach because it does not require any cumbersome modifications of FOM source codes35. With a non-optimal initial guess, the solver might not converge at all. Hence, using machine learning to assist this solver  could alleviate this. Recently, the use of machine learning to enhance, accelerate, or assist FOMs’ performance has been proposed. Some examples include (1) improving the efficacy of FOMs’ solver39, (2) guiding dynamic mesh refinement40, or (3) fine-tuning stabilization parameters42. Besides, there have also been other endeavors to speed up or stabilize a nonlinear solver; for instance, using data-driven modeling to accelerate pressure projection inside multi-grid solver43, residual smoothing, which aims to smooth any sharp gradients of Newton iterative steps44, or Krylov subspace algorithm, which aims to uses a low-rank least-squares analysis to search for equilibrium state of all degrees of freedom45. This paper proposes initializing FOM’s nonlinear solver by using ROM’s prediction. We hypothesize that as ROM’s prediction becomes closer to the real or converged solution of FOM, the nonlinear solver would require fewer iterations to converge compared to a conventional method of choosing an initial guess, resulting in a lower computational cost. Hereafter, we will refer to this technique as ROM-assisted FOM. We note that this approach is in line with using optimization algorithms such as genetic algorithm46, Powell’s method47, or chaos optimization algorithm48 to locate an optimal location of an initial guess.Even though ROM can deliver an acceptable accuracy with a much lower computational cost, it might not be suitable for an application in which precision is paramount. In such cases, FOM is still preferable. As mentioned previously, FOM’s solver can take a significant amount of computational resources, especially if the system is nonlinear. Besides, a solver of nonlinear PDEs relies heavily on the initial guess, preconditioner, or solving algorithmThe rest of the manuscript is summarized as follows. In “The summary of our proposed procedures is shown in Fig. 49 and magnetohydrodynamic50 equations using a solution of Stokes equations as an initial guess.Since every nonlinear solver step could be considered computationally expensive, we aim to reduce this computational cost by using ROM prediction ; for instance, contact problems or subsurface flow with wells is that there might be a very small part of a domain that is altered while the majority of it remains constant53. All ROMs used in this study are data-driven, or in other words, non-intrusive. Hence, the procedures proposed here, Fig. In this study, we generalize mentclass2pt{minim55 with a heterogeneous material   insee Fig. b, and  computed using Intel(R) Core(TM) i7-9750H CPU. As a result, the BBT-ROM model saves approximately 35 s per FOM evaluation, and the in-ROM saves approximately 50 s per FOM evaluation. The prediction time of the BBT-ROM model takes about 0.001 s, while the in-ROM takes around 8 s (both using the same Intel(R) Core(TM) i7-9750H CPU). Hence, the actual wall time saving for the in-ROM is 42 s. The training time of the BBT-ROM through NVIDIA Quadro RTX 5000 Mobile Max-Q is about 30 min. The training time of the in-ROM using Intel(R) Core(TM) i7-9750H CPU is about 60 min. We disregard discussion of the BT-ROM because it increases the computational burden .53. To elaborate, as we have only one point of contact, there is only a small area where the deformation occurs while most of the domain remains undeformed. In BBT-ROM we solve this problem by applying a boosting technique to the BT-ROM , fewer iterations of the nonlinear solver are required to reach convergence.Next, we use Similarly to the previous example , one nonlinear iteration takes approximately 10 s (63 s for 6.30 iterations) computed through Intel(R) Core(TM) i7-9750H CPU. Consequently, the BBT-ROM model saves us around 33 s per FOM evaluation, and the in-ROM saves us approximately 52 s per FOM evaluation. The prediction time of the BBT-ROM model takes about 0.001 s, while the in-ROM takes around 8 s (both using the same Intel(R) Core(TM) i7-9750H CPU). Hence, the actual wall time saving for the in-ROM is 44 s. Again, the training time of the BBT-ROM through NVIDIA Quadro RTX 5000 Mobile Max-Q is about 30 min. The training time of the in-ROM using Intel(R) Core(TM) i7-9750H CPU is about 60 min.In line with the previous example, we observe correlations between nonlinear iterations and relative error. To elaborate, a ROM that provides a more accurate prediction can assist in reducing a number of nonlinear iterations . The relative error results are presented in Fig. Lastly, we use the indentation location as our parameter, ] \in -0., 0.3 \tiThis setting has many more degrees of freedom than the previous two settings resulting in one nonlinear iteration computed through Intel(R) Core(TM) i7-9750H CPU taking approximately 35 s (or 215.6 s for 6.16 iterations). In short, using the in-ROM-assisted takes around 2.10 s more than the FOM default initialization . In contrast, compared with the zero-vector initialization, using the BT-ROM, the solver takes 26.60 s less, and using the BBT-ROM, the nonlinear solver takes 49.00 s less. The prediction time of the BT-ROM and BBT-ROM models is about 0.001 s (similar to two previous examples). The BT-ROM and BBT-ROM training times are approximately 60 and 55 min computed using NVIDIA Quadro RTX 5000 Mobile Max-Q, respectively. It is higher than the two previous examples because the number of degrees of freedom is substantially larger. The in-ROM takes 11 s per prediction resulting in the actual wall time incremental of 13.10 s. The training time of the in-ROM using Intel(R) Core(TM) i7-9750H CPU is about 110 min.25 for detailed discussions on linear and nonlinear manifolds. Furthermore, the BT models (BT-ROM and BBT-ROM) outperformed the in-ROM. In line with two previous settings, we still have only a small area of contact , resulting in BBT-ROM outperforming BT-ROM.Similar to two previous settings, there are correlations between a number of nonlinear iterations and relative error, see Fig. time-dependent two-phase flow in layered porous media. The details of the problem statement and governing equation can be found in Supplementary sec. 25. We fix the permeability of the bottom layer and set the porosity in the top and bottom layers to 0.1 and 0.2, respectively. We inject one phase on the left and produce both phases on the right by imposing a fixed pressure on both boundaries. The top and bottom boundaries are closed to flow. The viscosity and density of the injected and displaced phases are  are presented in Fig. We also present one additional benefit of using BBT-ROM-assisted, namely, cases that diverged using default initialization now converge—see Fig. We utilize a time-dependent phase-field modeling to capture fracture propagation for homogeneous material. The details of the problem statement and the governing equation can be found in Supplementary sec. Here, Example 4’s results are presented in Fig.  see Eq.  for \docThe cumulative nonlinear iterations for One additional point for this example is that most of the computational resources are allocated to states before and after fracture propagates for this type of problem. However, what we actually are interested in is (1) when the fracture starts to propagate and (2) when it ends. Hence, we believe that, for the future study, one can build ROM to approximate the fracture dynamics period (start and stop) and simply neglect the building up of energy (before the fracture propagates) period. This way, we can even further save our computational resources.Even though ROM can deliver a reasonable accuracy at a much lower computational cost, it might not be suitable for an application where precision is paramount. In this case, FOM or a high-fidelity model is still preferable. FOM, however, requires a substantial amount of computational resources, especially in a nonlinear system. Besides, it is not trivial to solve this nonlinear system since, with a non-optimal initial guess or solving algorithm, your solver might not converge at all. Hence, this work proposes a novel approach to achieve the accuracy of FOM performance and improve the convergence of FOM solutions with computational efficiency.We have illustrated the use of a low-fidelity model (or ROM) as an initial guess (ROM-assisted) to a FOM’s nonlinear solver, which can achieve speed up from 18 to 73% (cGAN-ROM for Example 1 and BBT-ROM for the rest), see Table We have summarized the normalized wall time magnitude, normalizing each wall time used by the highest wall time  and the relative error of ROM in Table 35, we have shown that ROM-assisted can converge all diverged cases . This characteristic is preferable and beneficial to many engineering applications.Another benefit of using ROM-assisted is it can improve the convergence rate. As a system of nonlinear PDEs is not straightforward to solve, and the convergence rate highly depends on the initial guess, preconditioner, or solving algorithm70 or incorporating physical information72 could reduce the required number of training data while maintaining similar accuracy. The cost of training of BT-ROM and BBT-ROM ranges from 30 to 45 min using a graphic processing unit (GPU), while the training of cGAN-ROM uses a significantly higher cost of 4 h through a GPU  as an initial guess to a nonlinear solver of full order modeling (FOM), we can reduce computation cost (fewer nonlinear iterations) and improve the convergence rate. To elaborate on these benefits, we showcase our framework through four different physics problems discretized by different numerical methods . Our results show that our approach speeds up nonlinear solvers by 18–73%. Besides, our framework improves the convergence of FOMs that would have otherwise diverged with default initial guesses. We want to emphasize that as our ROMs are data-driven and non-intrusive, we can apply them to any nonlinear physics-based problem.Supplementary Information.


ReValidate! wrist-rehabilitation game, which simultaneously acts as a digital goniometer. Furthermore, to establish the reliability of the game by contrasting ROM measurements to those found by medical experts using a universal goniometer.To determine the validity of wrist range of motion (ROM) measurements by the wearable-controlled As the universal goniometer is considered the reference standard, inter-rater reliability between surgeons was first determined. Internal validity of the game ROM measurements was determined in a test–retest setting with healthy volunteers. The reliability of the game was tested in 34 patients with a restricted range of motion, in whom the ROM was measured by experts as well as digitally. Intraclass-correlation coefficients (ICCs) were determined and outcomes were analyzed using Bland–Altman plots.Inter-rater reliability between experts using a universal goniometer was poor, with ICCs of 0.002, 0.160 and 0.520. Internal validity testing of the game found ICCs of − 0.693, 0.376 and 0.863, thus ranging from poor to good. Reliability testing of the game compared to medical expert measurements, found that mean differences were small for the flexion–extension arc and the radial deviation-ulnar deviation arc.ReValidate! game is a reliable home-monitoring device digitally measuring ROM in the wrist. Interestingly, the test–retest reliability of the serious game was found to be considerably higher than the inter-rater reliability of the reference standard, being healthcare professionals using a universal goniometer.The  MEC-AMC W17_003 #17.015. Previous research has shown that computer games are a promising adjunct to improve patient motivation in physiotherapy regimens –4. GamifDistal radius fractures are one of the most frequently occurring types of traumatic injury, making up 18% of fractures in patients presenting to the emergency department, and up to 25% of all fractures in the elderly patient group –12. DistReValidate! has been developed. The game is controlled by two wearable motion sensors, placed proximally and distally of the wrist, so that they bridge the wrist joint. Each sensor contains an accelerometer, a gyroscope and a magnetometer, enabling three-dimensional registration of movements in the wrist joint. The paired sensors act as controllers for playing the serious game Revalidate!, which is installed as a mobile application on a smartphone or tablet. The smartphone or tablet itself acts as the gaming platform. The ReValidate! game incorporates telemonitoring of the range of motion (ROM) of the wrist joint and of treatment adherence. In order for the in-game monitoring of patients’ progress to be safe during a clinical rehabilitation program outside of a research setting, and not pose a threat to patient privacy and data safety, the game must comply with medical device regulations [ReValidate! mobile game application, compared to the active ROM as measured by an experienced surgeon using a universal goniometer as the reference standard.To support patients in their rehabilitation process while simultaneously improving patient monitoring, the serious game ulations . The ROMulations . Other rulations . The uniulations . Newly dulations , 28. TheThe study was designed as an observational cohort study. The study was approved by the medical ethical review board of our institution (MEC-AMC W17_003 #17.015).A total of 34 patients suffering a restricted wrist ROM, and 7 healthy volunteers were recruited for this study. Patient characteristics are shown in the baseline table Table . The patReValidate! game application.For the purpose of determining internal validity of the electronic goniometer, sample size calculations were based on the intraclass correlation coefficient. To detect an intraclass correlation coefficient (ICC) of 0.9 when the null-hypothesis is 0.6, using a two-way mixed effects model, with a power of 80% and a significance level of 5%, seven participants were needed. The sample size to test external validity was in agreement with previous studies, and deemed to be sufficient in determining a difference in means of ROM of 5° between ROM measured using the digital game wearable goniometer, the goniometer measurements performed by experienced surgeons, with a significance level of 0.05 and a power of 80% , 29, 30.ReValidate! serious game is played on a tablet computer . The game is controlled by the wearable Valedo motion sensors . Alternatively, a version that can be played on a smartphone  and that is controlled using the Myo™ Armband  has been developed to meet the needs of patients not possessing both types of device. As the the Valedo® sensors were previously established to be reliable for range of motion measurements [The urements , and werUsing two separate motion sensors, placed both proximally and distally of the wrist joint, the isolated wrist joint motions can be used as game control, and ROM can be measured. Patients were instructed both orally as well as using pictures within the game, how to attach the sensors to their arm and hand. One sensor is securely strapped to the dorsum of the hand at metacarpal level, while the other sensor is securely strapped to the lateral side of the forearm, just distally to the elbow Fig. , so thatThe game is programmed to register both the maximum and average ROM values, as well as the complete motion ‘path’. By moving the wrist, the player controls an underwater avatar Fig. . For eacReValidate! game, a test–retest was performed using healthy volunteers. These volunteers were instructed to play the game and to reach their own maximum ROM during gameplay. To ensure the test–retest would not be influenced by confounding factors such as strain or exhaustion resulting from playing the game itself, volunteers were asked to play one complete level of the game twice, with at least 30 min of rest in between. The intraclass correlation coefficient (ICC) between the ROM as measured in the first and second gameplay session was determined using a two-way mixed-effects model .To establish internal validity of the goniometer embedded within the Directly after the two gameplay sessions, four experienced medical professionals were asked to measure the active ROM  in the healthy volunteers, using a universal  goniometer, as the reference standard. Experts had at least 5 years of experience and used the universal goniometer in their daily practice. To establish if measurements reported by the professionals using a universal goniometer can be considered reliable, the inter-rater reliability between the measurements of the participating professionals was tested. The experts were blinded to previously measured ROM outcomes, both as measured by the game and as measured by the other experts. Participants were instructed not to disclose any previous measurement outcomes. The inter-rater reliability was analyzed using a two-way random-effects model .ReValidate! game in patients with various levels of restriction in wrist ROM, as measured by highly experienced medical professionals using a universal handheld goniometer. Experts were two plastic surgeons and two trauma surgeons, all of whom were specialized in treating wrist injuries. All experts performed active ROM measurements in their daily practice. First, the maximum active ROM in the affected wrist joint of patients was measured by one of the experts. Subsequently, patients played a single level of the ReValidate! game using the same hand and maximum ROM outcomes were extracted from the game database.External validity was established by comparing ROM outcomes of the Concurrent validity between the game ROM outcomes and the ROM outcomes as measured by the experts was determined using a one-sample t-test to compare mean differences. Values were represented in means and standard deviations, p-values of < 0.05 were considered statistically significant. A difference in means of 5° was considered acceptable for reliable measurements. Scatter-plots and Bland–Altman plots were constructed to evaluate agreement and to assess for any systematic bias.All analyses were performed using the statistical package for the social sciences (SPSS) version 26 . ICC outcomes of 0.5 or lower were considered poor, 0.5–0.75 were considered moderate, 0.75–0.9 were considered good, and outcomes larger than 0.9 were considered excellent agreement.The test–retest reliability of the game, reflecting the internal validity of measurement outcomes established by the game was determined by calculating the intraclass correlation coefficient (ICC) using a two-way mixed-effects model . Even though patients are instructed to keep their wrist straight when calibrating the game and sensors, the neutral position can vary, since the game lacks visual analysis of movements. Therefore, the motion arcs are represented. Arcs are calculated by adding up the two maximum measurements of motions in opposite directions . Outcomes are represented in mean ROM and standard deviation, mean difference and ICC and 95% confidence intervals Table .Table 2TThough only the mean difference for the palmar-dorsal flexion is within the predefined 5° range, the mean differences are small, ranging from 1° to 8°. There were no significant differences between the test and retest. Intraclass correlations range from poor (0.376) for the pronation-supination arc, to good (0.693–0.863) for the palmar-dorsal flexion and radial-ulnar deviation arcs.To evaluate the reliability of ROM measurements by experienced professionals using a universal goniometer, the inter-rater reliability was determined. Measurements were registered in degrees. Means and standard deviations between the medical professionals showed large variations, especially in the palmar-dorsal flexion and pronation-supination arcs . Though the measurements showed more agreement in the radial-ulnar deviation arc, there was still a considerable variation and the ICC was only moderate (ICC 0.52). Outcomes of the inter-rater reliability ) are represented in Table Mean differences were calculated by determining the difference between the ROM measured by the game and measured by the expert (game outcomes–expert outcomes). Mean differences were tested using a one-sample T-test to determine their difference to zero, with zero being the ideal outcome (meaning a perfect agreement between the doctors’ and the game measurements). Outcomes are represented as mean difference, 95% confidence interval of the mean difference and the significance level Table .Table 4MScatter plots show the agreement between the two measurement techniques Fig. . Though ReValidate! game for wrist rehabilitation has previously shown to be valid in home-based patient care for training active range of motion in patients having suffered a distal radius fracture and has the potential to improve rehabilitation outcomes [The outcomes . To safeoutcomes .ReValidate! game and evaluated in this study, are therefore sufficiently reliable to be used in patient home-based monitoring, compared to ROM measurements as performed by an experienced medical professional.This study shows a good test–retest reliability  for the radial-ulnar deviation and palmar-dorsal flexion arcs, as measured during repeated playing sessions of the game. Pronation and supination test–retest outcomes are less reliable and show considerable variation between the gameplay sessions. External validity testing, comparing game outcomes to measurements by experts, shows a good comparability for radial-ulnar deviation and palmar-dorsal flexion arcs. Though the limits of agreement are wider than the ideal level of 5°, the variation can also be attributed to the variation in measurements between medical professionals. The motion sensors  used for controlling the ReValidate! mobile game application can be seen as a valid monitoring tool for dorsal-palmar flexion and radial-ulnar deviation, as the mean differences between the game and the medical professionals are within the 4°–6° range. A restriction in ROM in the wrist has been shown in previous studies to be associated with lower functional scores [Regarding monitoring in a home-based rehabilitation setting, the l scores , 35. Reml scores . A succeIt is striking that the participating medical experts, all with at least 5 years of experience and experienced in using a universal goniometer in daily practice, show significant variation in measuring active ROM of the wrist (ICC varying between 0.02 and 0.52). These measurements are the most frequently used type of measurement for wrist range of motion, next to visual estimation, and are therefore considered the ‘gold standard’ by some. As they are used as a reference for the results of the game, these variations inevitably influence outcome of the study. Previous studies show that the inter-rater reliability is dependent on the measurement technique used and the experience and training of the medical professional , 40. CauWith previous research mainly focused on flexion and extension measurements as a tool for monitoring rehabilitation progress , the queWhile it is a limitation that the game is currently only available for Apple™  devices, this choice was made as Apple™ HealthKit™  can directly send data to the Epic® electronic health records . This will allow physicians immediate access to game data, including progress reports and treatment adherence details. Though the smartphone version of the game has not been tested for reliability of goniometric measurements, this version still allows for home-based monitoring of treatment adherence. The game has been developed specifically for compatible smartphones and tablets, and follows the ‘bring your own device’ principle. This principle means that when the game is compatible with more different types of mobile devices, more patients are enabled to practice their rehabilitation exercises using the game. The game will therefore be expanded to be compatible with other types of devices in future development.It can also be considered a limitation of this study the ROM measurements by experts contain too much ‘human error’. Though these measurements are commonly used to monitor patients’ rehabilitation progress in daily medical practice, they seem too inconsistent be considered to be the gold standard for ROM measurements.ReValidate!, which incorporates a digital goniometer, shows a higher reliability and validity in measuring active ROM of the wrist joint. This study shows that medical professionals, including surgeons and hand therapists, can rely on a commercially available off-the-shelf tool to reliably monitor the progress of their patients participating in a home-based rehabilitation program, without requiring hospital visits for monitoring. Especially during a worldwide pandemic, with restricted access to healthcare and where social distancing rules apply, this is an interesting development.In this study, experienced healthcare professionals’ measurements show a poor inter-rater reliability using a universal goniometer in measuring active ROM of the wrist. In contrast, the wearable-controlled mobile game


There were recent reports of a mysterious virus spreading in Pakistan causing dengue-like illness with hundreds of cases admitted to hospitals over the winter. The mysterious virus was touted as a new variant of the dengue virus by the local health experts in Pakistan as most patients were tested negative for the dengue virus test despite presenting with dengue-like symptoms. In this letter, we have critically appraised the current situation in Pakistan in an attempt to explain the science and mechanism behind recent dengue-like outbreak, offered suggestions on diagnostic tests and provided recommendations to improve medication safety in Pakistan. Dear Editor,Khatri et al. recently wrote on simultaneous crises for dengue and Covid in Pakistan debilitating the country’s healthcare system . In addiIt is not uncommon for viruses to mutate and evolve genetically, significant molecular changes on viral proteins can affect specificity of the molecular diagnostics. For instance, NS1 antigen tests that are commonly used in Pakistan to diagnose DENV detects the non-structural protein NS1 of the dengue virus, usually found in the patient’s blood during dengue infection. This test contains synthetically labelled antibodies that binds specifically to the NS1 proteins in blood to confirm the presence of dengue virus. Significant mutations in dengue virus would mean that the diagnostic antibodies will not be able to bind to the circulatory proteins of the dengue virus rendering NS1 test false negative. In practice, this would usually lead to the revision of the molecular diagnostics with time as the virus evolves.It is also important to understand that NS1 is only detectable during the acute phase of the dengue virus infections. Therefore, NS1 is likely to return false negative after 7 days of symptoms. Nucleic acid amplification test (NAAT), for example PCR, should be used in this instance that is a preferred diagnostic test for dengue over NS1 antigen test, as it can provide confirmed evidence of infection in the initial phase . DENV-spIt is also possible that this mysterious dengue-like illness may not be dengue fever at all. Instead, this could be Covid-induced thrombocytopenia, which can often manifest clinically similar to the dengue fever. This is particularly possible in an event of coinfection with a seasonal winter bug  prevalenThe healthcare professionals in Pakistan are also urged to report all suspected adverse events following Covid vaccines to the National Pharmacovigilance Centre in Pakistan to help with vaccines pharmacovigilance to support global regulatory and public health agencies in  improving medication safety.


Chikungunya virus (CHIKV) belongs to the genus Alphaviridae, with a single-stranded positive-sense RNA genome of 11.8 kbp encoding a polyprotein that generates both non-structural proteins and structural proteins. The virus is transmitted by the Aedes aegypti and A. albopictus mosquitoes, depending on the location. CHIKV infection leads to dengue-like musculoskeletal symptoms and has been responsible for several outbreaks worldwide since its discovery in 1952. Patients often experience fever, headache, muscle pain, joint swelling, and skin rashes. However, the ultrastructural and mechanical properties of CHIKV have not been fully characterized. Thus, this study aims to apply a physical approach to investigate CHIKV′s ultrastructural morphology and mechanical properties, using atomic force microscopy and Raman spectroscopy as the main tools. Using nanomechanical assays of AFM and a gold nanoparticles substrate for Raman signal enhancement, we explored the conformational plasticity, morphology, vibrational signature, and nanomechanical properties of the chikungunya virus, providing new information on its ultrastructure at the nanoscale and offering a novel understanding of the virus’ behavior upon mechanical disruptions besides its molecular composition. Chikungunya virus (CHIKV) is a single-stranded RNA alphavirus with a reported diameter of approximately 70 nm . These vStructural investigation of viruses supported by high-resolution microscopy techniques has been a breakthrough in uncovering new aspects of viral structural components and functions. Nevertheless, there are complexities related to the dynamic nature of viruses that do not fit into static glimpses . Still, Therefore, studying mechanical properties could clarify the relationship between the structure and function of viral particles. Atomic force microscopy (AFM) is a powerful technique that can be used to investigate these mechanical properties at the nanoscale ,16 and, v/v) penicillin/streptomycin (Gibco)-M10) for 48 h. Then, the supernatant of infected cells was collected, harvested, and titrated as previously described. The virus was inactivated by thermal treatment at 56 °C for 1 h [A Brazilian isolate of the CHIKV ECSA strain (Genbank: KP164569) was propagated in Vero E6 cells  in MEM medium (Gibco)  and 1% . The spectrum was acquired after three acquisitions of 30 s in each dispersion band of the spectral grid [The Raman scattering measurements were performed on a micro-Raman system, model T64000 (Horiba/Jobin-Yvon), operating in the single mode. A 2 mW diode laser operating at 785 nm was used as the excitation source. A neutral density filter (1%) was used to avoid laser-induced damage to the sample. The light was focused on the sample using a microscope model BX41 (Olympus), with a 100× objective lens , and the Raman signal was dispersed in an 1800 gr/mm grid and detected in a liquid-nitrogen-cooled CCD. The slits of the spectrometer were adjusted to obtain a spectral resolution of 2 cmral grid ,24.This study investigated the plasticity, morphology, and adhesion properties of CHIKV providing new information on its ultrastructure at the nanoscale and offering an understanding of the virus’ behavior upon mechanical disruptions. The high-resolution topographic maps revealed the structures of the viral surface and its protein distribution A. It is Viral particles are not rigid solids, although CHIKV mainly comprises closely packed glycoproteins that form the icosahedral capsid. As an enveloped virus, there is a lipidic layer involving the protein capsid in which the surface proteins are anchored . PhysicaFor the adhesion map, the lighter regions B,D are a3N4) with well-defined specifications, such as geometry and tip radius, and the same conditions for all the assays performed, including temperature and air humidity.Adhesion maps are related to the probe and sample surface interaction forces. It could also detect interactions between the different structures of the particle itself. These adhesive interactions are electrostatic, van der Waals and capillary forces, and forces promoted by chemical bond breakage . UsuallyPrevious literature  on the sFor each indentation cycle, a force curve was obtained as a result of the approximation and retraction movement of the probe relative to the sample. In Throughout our AFM analyses, we observed the formation of fibers  in diffeAs for a reason for the appearance of these fibers, it is possible that some CHIKV particles have collapsed, and the genetic content from inside the capsid has spilled out and formed these fiber-like structures. Another feasible explanation is that, upon collapsing, E1 and E2 glycoproteins in the CHIKV capsid can re-arrange together with the genetic content to form these fiber structures. Literature reports similar structures related to protein self-assembly  and someIt is worth noting that we did not observe the formation of these fiber-like structures when analyzing other viruses ,11, despTo identify molecular compositions and provide a vibrational signature of CHIKV particles and these newly identified fiber-like structures, we performed SERS measurements. In the spectra obtained , it was −1), proline (937 cm−1), and L-tyrosine (1200 nm−1) that can be related to the glycoproteins [−1) and lipids (1305 cm−1 and 1450 cm−1) that relate to the composition of the viral membrane [−1 to 1260 cm−1, there is the presence of the amide III band assignment. The amide group is associated with the functional group CONH (carbon-oxygen-nitrogen-hydrogen), which essentially creates linkages for protein formation, conferring structural rigidity [The two peaks of phosphodiester (O-P-O) around 800 cm-1 are related to the RNA backbone, which links the nuclear bases . In addiproteins  on the smembrane ,44. In trigidity . The amirigidity .The non-appearance of the amide I band is noteworthy in the spectra obtained, which is representative of protein domains in Raman spectroscopy results. This absence is related to the length of the amino acid side chain. The side chains increase the distance between the peptide bond and the metallic nanoparticles, preventing them from coming into direct contact. However, it is also possible that the lack of the viral amide spike is also related to the virus, an inactivation program that breaks down amino acids .It is important to point out that, for label-free SERS measurements, it is virtually impossible to know whether the laser hits a virus particle since the positioning of the laser is performed with the use of an optical microscope that is not even near the necessary resolution to spot a viral particle. A solution for this could be using a tip-enhanced Raman spectroscopy (TERS) measurement as performed by Dou and collaborators , where tThis study provides findings regarding the chikungunya virion diameter (~52 nm), the stiffness of the particle, and the amount of force one viral particle can withstand when subjected to mechanical loads, which is about 25 nN, demonstrating a strong and stiff behavior compared to previous tested viral particles in same conditions. Additionally, a unique fiber formation was found in the viral sample, with lengths over 500 nm and a building block periodicity of around 37 nm. The CHIKV particle demonstrates a plasticity behavior upon mechanical stress and a positive charge distribution around most of its surface, besides some negative spots that are probably related to interactions between the surface proteins. Moreover, the SERS measurements provide viral particle composition and a vibrational signature. In the spectra, it was possible to identify the main bands related to RNA bases, as well as protein-related bands. The finding of the fiber-like structures can shed light on the relationship between CHIKV infection and pathologies related to collagen-rich sites in the body. These results and the analysis of the biomechanical characterization of this virus can aid in better understanding its pathophysiology, adding new data in the description of the physical and structural properties of CHIKV, corroborating models shown in the literature, and providing new insights that can be useful in designing strategies to fight this infectious agent. The findings presented here are of pronounced importance because once we understand these mechanisms, we can find specific drugs or biomolecules that could weaken this viral particle, which is extremely resistant. Moreover, based on the properties observed, such as vibrational modes and adhesion forces, we might be able to understand more about the target sites and the mechanisms of action of the Chikungunya virus.


The molecular mechanism of hepatitis E virus (HEV) pathology is still unclear. The micro RNAs (miRNAs), of host or viral origin, interfere with virus replication and host environment in order to create an appropriate condition for the production of mature HEV progeny. Understanding the biogenesis and the interference of miRNAs with HEV will help to revile the mechanism of viral pathogenesis. Micro RNAs (miRNAs) are a class of small non-coding RNAs that are conserved in eukaryotes and are essential in the control of translation and transcription rate. In humans, they are crucial for cell differentiation during embryogenesis, for cell–cell communications and for immune response to infections. At the same time, they interact with different pathological processes as cancer development or a generate environment suitable for pathogens’ replication. In recent years, evidence for the role of miRNAs in viral replication and adaptation has accumulated. The first viral miRNA was detected in cell culture system during latent Epstein–Barr virus infection ; since tHepatitis E virus (HEV) is transmitted mainly by the fecal–oral route and is the causative agent of acute viral hepatitis worldwide. HEV is classified into eight genotypes , as HEV ORF)). From all genotypes, which infect humans, HEV-3 is characterized by high variability [ORF1 [HEV is a positive sense single-strand RNA virus, in which the virion presents in two forms: enveloped and non-enveloped. The viral genome contains three open reading frames , HEV belongs to species iboviria . Recentliboviria : genotypiboviria . In Euroiboviria . Until riboviria ,12,13. Hiboviria .ORF1, ORF2 and ORF3, flanked with untranslated regions (UTR). For HEV-1 the transient translation of ORF4, during endoplasmic reticulum stress, has been identified [ORF1, which is the largest one, with structural domains for methyltransferase (Met), Y domain (Y), papain-like cysteine protease (PCP), hypervariable region (HVR), X domain (X), helicase (Hel), and the RNA-dependent RNA polymerase (RdRp), is translated by the cap-dependent mechanism directly from the positive HEV RNA into a polyprotein [ORF2 and ORF3 [ORF2 encodes viral capsid proteins. ORF3, which is overlapping ORF2, encodes a small phospoprotein that facilitates the virions release in the quasi-enveloped form [ORF1 is the most susceptible to recombinant events, insertions and deletions, as the last are typical for HVR. Examples for insertions, with host origin, are the Kernow-C1 HEV-3 strain that contains 171-nucleotide segment of the S17 human ribosomal protein gene, and HEV strain containing fragments from the human S19 ribosomal protein gene, and from the human TAT and ITI-H2 genes [RdRp domain and are connected with treatment failure as virus adaptation to the changing environment [Hel and X domains of ORF1 [Hepatitis E virus is a single-stranded RNA quasi-enveloped virus that in bile and feces is non-enveloped (neHEV) and in blood circulates as an enveloped form (eHEV). Its genome consists of three open reading frames – entified . 5’-UTR entified . The entyprotein . Servingand ORF3 ,17. ORF2ped form . ORF1 poped form , and incped form . At the ped form . The undped form . In factH2 genes . All strironment . Recombi of ORF1 .HEV is a primary hepatotropic virus, but hepatitis E virus infection can also proceed with extrahepatic manifestations, such as neurological and renal diseases, hematological disorders, pancreatitis, myocarditis, arthritis and autoimmune thyroiditis . In the miRNAs are small (up to 25 nt), non-coding highly conserved RNAs, which represent 1% of the human genome but interact with about 60% of messenger RNAs . The matPicornaviridae, Hepadnaviridae, Kolmioviridae, Flaviviridae, and Hepeviridae [Viral hepatitis—hepatitis A virus (HAV), hepatitis B virus (HBV), hepatitis D virus (HDV), hepatitis C virus (HCV) and HEV— are hepatotropic viruses belonging to different families: eviridae . HAV, HDHepatitis C virus is a positive sense RNA virus, whose genome contains one ORF, flanked by 5’ and 3’ UTRs. Within 5’-UTR, the internal ribosome entry site is located, which is essential for cap-independent translation of the HCV genome . In 5’-UHBV is a small DNA virus, with partially double-stranded relaxed circular DNA, comprised of four overlapping ORFs. The HBV DNA is replicated by reverse transcription and the formation of pregenomic RNA. Cellular miRNAs act directly with HBV transcripts or indirectly by targeting cellular factors relevant to the HBV life cycle. In most cases, direct acting mi-RNAs—miR-122, mir-125 family, miR-199a-3p, and miR-210—inhibit HBV replication, which is supposed to be associated with the establishment of persistent HBV infection . At the Till now, the possible encoding of viral miRNAs by HDV has not been well studied. The HDV genome is a single-stranded negative-sense covalently closed circular RNA molecule with approximately 74% base pairing. It is hypothesized that HDV is a result of the recombination between a viroid-like element and a host mRNA . At the HAV is a typical cytoplasmic virus that is nonlytic and is released as an enveloped form in the patient’s serum and cell supernatant and as a non-enveloped form in feces . In factAs can be summarized, the interplay between hepatitis viruses and viral or host miRNAs can be direct, by complimentary binding between miRNA and viral target sequence, or indirect, by alteration of the host signal pathway during virus invasion and replication. In the case of HCV, the liver miRNAs are essential for viral genome stabilization and the establishment of persistent infection with maintenance of low viral replication. For HBV and HAV, these interactions are focused on persistent infection. Thus, it can be hypothesized that hepatitis virus liver tropism appears to be due to the positive effect of liver miRNAs.In addition to viral transcripts, HEV produced several different miRNAs. Till now, their study has mainly been based on prediction in silico models confirmed by in vitro or in vivo experimental infectious models. At present, these studies are hampered by the absence of a suitable infectious model, as HEV replicates slowly in cell-cultured systems, leading to virus adaptation .MeT domain  and within ORF2. HEV-miRNAs target sites are proposed to be located at both 3’-end and 5’-end of human mRNA. The targeted silencing has been proposed for genes, essential in chromosome organization, cell differentiation, lipid and nitrogen metabolism, membrane organization and transmembrane transport, and cell–cell signaling. From all nine predicted HEV-miRNAs, five—HEV-MD1, HEV-MD2, HEV-MD25, HEV-MD31 and HEV-MR10—affect membrane organization and transmembrane transport [Using computational prediction modeling, nine potential HEV-miRNAs—HEV-MD1, HEV-MD2, HEV-MD3, HEV-MD25, HEV-MD31, HEV-MD-35, HEV-MD39, HEV-MR9 and HEV-MR10—were identified for HEV-1 . Positioransport . As was ransport , which cransport , which iransport . The memransport , which sPrediction models for human host miRNAs, targeting HEV genome, are based on previously studied miRNA signatures in viral hepatitis infection, such as HCV and HBV, and on host miRNA cell-, organ-, and tissue-specific patterns. To date, the most extensively studied host miRNAs affecting HEV replication are miR-122 and miR-214.In humans, the gene coding miRNA-122 (miR-122) is located within chromosome 18. As it was described above, miRNA-122 is the most represented in the human liver, and its role was extensively explored in liver cell differentiation, in cholesterol metabolism, as in liver pathogenesis, due to HCV- and HBV-induced hepatocellular carcinoma. RdRp region from the ORF1 gene  is located in a chromosomal region 1q24.3, in intron 14 of the Dynamin-3 gene (DNM3) . MiR-214PCP, HVR, Hel and RdRp domains at ORF1  by directly binding to the viral genome; (2) indirectly, by stimulating the secretion of pro-inflammatory cytokines; or (3) by stimulating changes in the miRNA pattern at the cell or tissue level .The miRNA-specific signature, that is characterized with a specific miRNA pool, was described for different human tissues . For exaThe miRNAs cannot be detected only in tissues or specific cells; they circulate in the serum and other different extracellular bio-fluids, such as cerebrospinal fluid, saliva, tears, urine, peritoneal fluid. They are characterized by a typical expression profile in healthy individuals . ChangesORF1, which encodes non-structural viral proteins essential for viral replication. This is the most heterogenic/variable region from the HEV genome prompt to naturally occurring recombination, insertion or deletion. Zoonotic genotypes, HEV-3 and HEV-4, that infect humans and a broad range of animal species, are characterized with higher intra-species variability in comparison with HEV-1 and HEV-2 genotypes that infect only humans. Recombination usually occurs in the Hel domain of ORF1, as insertions, which can be of viral or host origin happen in the HVR domain [As can be seen, HEV has adapted to host miRNA action in order to enhance replication and the production of mature progeny. HEV-miRNAs are acting mainly on later stages and facilitate the excretion and dissemination of the infectious progeny. In fact, the HEV-miRNAs coding sequences, as host miRNAs binding sites, are located predominantly in R domain . Usually


We describe the characterization of an African swine fever genotype IX virus (ASFV-Kenya-IX-1033), which was isolated from a domestic pig in western Kenya during a reported outbreak. This includes the efficiency of virus replication and in vivo virulence, together with genome stability and virulence, following passage in blood macrophages and in a wild boar lung cell line (WSL). The ASFV-Kenya-IX-1033 stock retained its ability to replicate in primary macrophages and retained virulence in vivo, following more than 20 passages in a WSL. At the whole genome level, a few single-nucleotide differences were observed between the macrophage and WSL-propagated viruses. Thus, we propose that the WSL is suitable for the production of live-attenuated ASFV vaccine candidates based on the modification of this wild-type isolate. The genome sequences for ASFV-Kenya-IX-1033 propagated in macrophages and in WSL cells were submitted to GenBank, and a challenge model based on the isolate was developed. This will aid the development of vaccines against the genotype IX ASFV circulating in eastern and central Africa. African swine fever (ASF) is a hemorrhagic disease of pigs, which causes up to 100% mortality in naïve domestic pigs. Although African swine fever virus (ASFV) has been endemic in sub-Saharan Africa (SSA) for decades, other parts of the world are also affected. In SSA, multiple genotypes, based on the variable c-terminal sequence of the gene encoding the p72 major surface antigen ,4,5,6. FEfforts are being made to develop vaccines against this devastating virus, with most efforts focused on the genotype II ASFV, which is currently circulating in Europe, Asia, and Hispaniola. The most promising candidate vaccines are live-attenuated African swine fever viruses (LA-ASFV), which have shown to provide up to 100% protection against challenges from homologous pathogenic ASFVs ,12,13. TOne of the challenges with the development of LA-ASFV is the difficulty of growing ASFV in vitro. ASFV is normally grown in primary cells, such as blood-derived macrophages or pulmonary alveolar macrophages. However, the use of a continuously growing production cell line is desirable, since this allows improved quality control. However, prolonged passage in tissue culture can alter the ASFV genome, the in vitro characteristics of the virus, and/or the in vivo characteristics ,15,20.The wild boar cell line (WSL) is isolated from lung tissue and grows continuously without the addition of any propagating factors. It was originally described as a pulmonary macrophage line , but a lASFV-Kenya-IX-1033 was isolated from the spleen of an infected domestic pig from the Busia district in western Kenya . The iso2 for 5–7 days. Cells and supernatant were harvested from flasks, and cells were lysed by repeated freeze-thawing three times. The virus-containing supernatant was clarified by centrifugation at 670× g for 10 min and aliquoted and stored at −80 °C. Stocks were titrated using HAD50 assay in pulmonary alveolar macrophage (PAM) cells, isolated as described by Zhang et al. [50 assay in WSL cells.The WSL-grown virus (p20) was transferred back to the International Livestock Research Institute (ILRI) in Nairobi, Kenya, where it underwent two additional passages in WSL. The WSLs were kindly provided by Matthias Lenk from the Friedrich-Loeffler-Institute (FLI), Greifswald-Insel Riems, Germany. It is not commercially available. For each passage, WSL cells were infected at 80% confluence with a multiplicity of infection (MOI) of 0.1, in either T25 or T75 flasks, and incubated at 37 °C and 5% COg et al. , or by T2 for 5–7 days. Cells and supernatant were harvested from the flasks, and cells were lysed by repeated freeze-thawing three times. The virus-rich supernatant was clarified by centrifugation at 670× g for 10 min, and the clarified supernatant was aliquoted and stored at −80 °C. Stocks were titrated using HAD50 assay in PAM.The macrophage-grown virus stock of ASFV-Kenya-IX-1033 underwent a total of four passages in blood macrophages. For each passage, blood macrophages were infected at MOI 0.1, in either T25 or T75 flasks, and were incubated at 37 °C and 5% COg for 2 h at 4 °C to pellet the virus particles in a Beckman Coulter Avanti Centrifuge J-301. The pellet was resuspended in 3 mL of 10 mM Tris (pH9), and the virus suspension was layered on 36% sucrose solution and subjected to ultracentrifugation at 30,000× g for 2 h at 4 °C, using the Beckman Coulter Optima XE-90 ultracentrifuge. The pellet containing the purified virus was resuspended in 10 mM Tris (pH9) and aliquots were stored at −80 °C.For whole-genome sequencing, the clarified supernatants containing ASFV, for both the WSL-grown and the blood macrophage-grown virus stocks as described in the previous section, were further purified using a 36% sucrose solution. The supernatant was transferred into autoclaved, 250 mL, flat-bottom ultracentrifuge tubes, followed by centrifugation at 18,500× DNA was extracted from the sucrose-purified virus using the Qiagen DNeasy blood and tissue kit , according to the manufacturer’s protocol. Whole-genome sequencing was performed using the Illumina MiSeq platform at ILRI, as described previously . Reads wTo verify SNPs and indels in the whole genome sequence, loci of interest were amplified, with respective primer pairs Table A12 in duplicate wells of a 24-well plate. After 2 h of incubation, cells were washed twice in 1× PBS to remove non-attached and non-internalized viruses, before the addition of the complete medium  or DMEM for WSL-, supplemented with 2 mM L-glutamine , 10% fetal bovine serum (FBS), 100 UI/mL penicillin (Sigma Aldrich), and 100 mg/mL streptomycin ). Cells and supernatant were harvested at 2, 24, 48, 72, and 96 h after infection and frozen at −80 °C until further analysis. After 3 freeze–thaw cycles, viral titers were established using HAD50 assay using PAMs. Viral titers in the supernatant were measured on the same day for consistency in results.WSL cells and PAMs were infected with either the blood macrophage- or the WSL-grown virus stocks at different multiplicities of infection (MOI) and incubated at 37 °C and 5% CO2 HAD50 of the blood macrophage-propagated virus stock or 102 TCID50 of the WSL-propagated virus stock. Infected animals were monitored daily, and clinical scoring was performed daily, according to King et al. [All animal experimental work was approved by the ILRI Institutional Animal Care and Usage Committee . Pigs did not have detectable ASFV DNA copies in EDTA blood by qPCR and were seronegative, as determined by a competitive p72 ELISA  prior to the start of the experiment. Groups of 5 animals were inoculated by intramuscular injection in the neck with 1 or 1050 assay. The virus containing samples were 10-fold serial diluted in complete RPMI (described above) and added to PAM in 96-well plates, in 4 replicates per dilution. The presence of the virus was assessed by hemadsorption at day 5, after the addition of red blood cells and viral titers were calculated by the Spearman–Kärber algorithm, as described/reviewed in Ramakrishnan et al. [Virus titers of viral stocks and experimental samples were determined by HADn et al. .p72/B646L qPCR was used to assess the virus DNA content in tissue samples. DNA was extracted from tissue using the Qiagen DNeasy blood and tissue kit , according to the manufacturer’s protocol. qPCR was performed as per the OIE-recommended real-time PCR assay, according to King et al. (2003) , but priThe growth kinetics of the blood macrophage-grown and WSL-grown viruses were compared using a two-way ANOVA for growth in macrophages and for growth in WSL. A comparison of their survival was tested using a Mantel-Cox log rank test. A two-way ANOVA was used to analyze the viral growth kinetics. The time to first detection of virus in serum, the time to maximum viral titer in serum, the time to humane endpoint, and the CT values in tissues were analyzed using a one-way ANOVA. All statistical analyses were performed using Graphpad Prism version 8, .6 HAD50/mL for the two stocks after 96 h . Growth in WSL cells was less efficient for both the blood macrophage- and WSL-propagated virus stocks; the virus was only detected after 96 h when using an MOI 0.01 with a wash step after 2 h. However, when the MOI 1 was used (8 HAD50/mL vs. 3.9 × 1011 HAD50/mL), albeit this was not statistically different . When testing the viral titers after 4 days of in vitro culture using different a MOI of the virus, without a wash step after infection, we observed the same tendency as seen in 6 HAD50/mL and 1.7 × 108 HAD50/mL for the blood macrophage-propagated and the WSL-propagated virus, whereas at MOI 5, both stocks had the same viral titer (1.7 × 109 HAD50/mL) . PAMs were infected with the two virus stocks at a MOI of 0.01. Similar growth  was seen for both the macrophage-grown stock and the WSL-grown virus in the PAM, with final titers of approximately 5 × 10ter 96 h A  C.50 or 102 HAD50 of the macrophage-propagated ASFV-Kenya-IX-1033 or 102 TCID50 of the WSL-propagated ASFV-Kenya-IX-1033. Both the macrophage- and the WSL-propagated virus stocks were highly pathogenic in vivo. All animals developed severe clinical signs compatible with ASF. There was no statistical difference between the final survival of the groups inoculated with the high dose of either the blood macrophage- and the WSL-propagated ASFV-Kenya-IX-1033 viruses using a Mantel-Cox log-rank test (p = 0.395). However, a delay in the clinical outcome was observed in animals inoculated with a lower dose of 1 HAD50 of the blood macrophage-grown stock (Mantel-Cox log-rank test (p = 0.0017). The animals reached their humane endpoint between day 9 and day 16 after infection with 1 HAD50 (p = 0.001 using one-way ANOVA).To investigate if the propagation of the virus in different cell types affected the virulence/pathogenicity of the virus in vivo, animals were infected by intramuscular injection with 1 HAD 1 HAD50   . There were no differences in maximal titers of the virus in the serum between the three groups (p = 0.45), and no differences were observed between the three groups in CT values obtained by p72-qPCR, using DNA from tissues harvested after euthanasia/death (p = 0.616)  A,C. Howe= 0.002) A,C. Simi= 0.616) B.Gross pathological findings were compatible with acute African swine fever for animals inoculated with both the ASFV-Kenya-IX-1033 grown in the WSL and ASFV-Kenya-IX-1033 grown in blood macrophages . FindingAs there were limited in vitro and in vivo differences between the macrophage-grown and WSL-grown ASFV-Kenya-IX-1033 stocks, whole-genome sequencing was performed to establish the degree of genomic changes between the stocks. DNA from macrophage- and WSL-grown viruses was sequenced using the Illumina MiSeq platform, which yielded 2.9 M and 3.3 M paired-end reads, respectively. After the removal of short, low-confidence reads and those derived from the host, about 700,000 (13.3%) and 1.2 M (18.8%) reads remained, which were assembled de novo. Both the macrophage- and WSL-grown virus genomes assembled into two contigs, the total number of bases assembled being 182,424 bp and 182,038 bp, respectively. The two contigs were separated by a break of 293 bp and 678 bp in the N-terminal region of the CD2v gene in the two genomes, respectively. To check whether the contig break was due to a deletion in the virus DNA or an anomaly arising from the sequencing, we designed PCR primers flanking the putative breaks Table A1A high level of nucleotide identity (>99%) between the two ASFV-Kenya-IX-1033 stocks was observed across the genome, with four single-nucleotide polymorphisms (SNPs) present in the aligned regions . Of the The genomes of the two ASFV-Kenya-IX-1033 stocks were annotated based on the Ken06.Bus strain . Sequenc2 HAD50, animals reached the humane endpoint criteria between 5 to 8 days post injection, and this was reproducible over several experiments. Even at a dose of 1 HAD50, all animals reached the humane endpoint between 9 to 16 days post challenge.In eastern Africa, multiple genotypes of ASFV are concurrently circulating, with genotype IX and X being responsible for most outbreaks ,4,26. AdThere are several promising candidate vaccines based on the LA-ASFV, which show protection against homologous ASFV challenges, with up to 100% protection. One of the challenges with the development of LA-ASFV is the difficulty of growing ASFV in vitro. ASFV is traditionally grown in primary cells, such as blood-derived macrophages or PAMs. However, a continuously growing cell line for the propagation of ASFV would substantially reduce the cost for vaccine production and allow improved quality control. However, prolonged propagation in continuously growing cell lines can lead to genomic changes. Growth of ASFV in Vero cells, which is an immortalized primate cell line, resulted in large deletions in the ASFV genome as the virus adapted to the cell line . In the 11 HAD50/mL were obtained using the WSL-propagated stock. Sanchez et al., found that ASFV viruses could grow in a PAM and WSL with lower titers at 12 h post infection in WSL cells for most viruses compared to PAMs, but similar viral titers were found for the viruses tested later, after in vitro infection (>48 h)  [Both the blood macrophage- and the WSL propagated ASFV-Kenya1033-IX can infect WSL, but a tendency to lower viral titers were obtained for the blood macrophage-propagated virus compared to the WSL-propagated virus . We also observed lower final titer when a lower MOI was used, which simply may be related to a delayed replication. Viral titers of up to 3.9 × 10and E70) . In thisand E70) . TherefoKeßler et al. investigated differences in the intracellular ASFV proteome after the infection of different cell lines  and found considerable quantitative differences in the expression of viral proteins, depending on the type of infected cells . DecipheIn conclusion, the Kenyan ASFV isolate ASFV-Kenya-IX-1033 is a highly virulent virus, and this virulence is maintained after in vitro passage in WSL cells. Furthermore, the virus genome is stable after passage in WSL cells, and high viral titers can be obtained. Thus, the WSL could be a suitable cell line for the future production of LA-ASFV vaccine candidates, although there may be substantial differences dependent on the particular virus isolate, which would need to be tested on an individual basis.


Leucine-rich Glioma-Inactivated protein 1 (LGI1) is expressed in the central nervous system and its genetic loss of function is associated with epileptic disorders. Additionally, patients with LGI1-directed autoantibodies have frequent focal seizures as a key feature of their disease. LGI1 is composed of a Leucine-Rich Repeat (LRR) and an Epitempin (EPTP) domain. These domains are reported to interact with different members of the transsynaptic complex formed by LGI1 at excitatory synapses, including presynaptic Kv1 potassium channels. Patient-derived recombinant monoclonal antibodies (mAbs) are ideal reagents to study whether domain-specific LGI1-autoantibodies induce epileptiform activities in neurons and their downstream mechanisms. We measured the intrinsic excitability of CA3 pyramidal neurons in organotypic cultures from rat hippocampus treated with either an LRR- or an EPTP-reactive patient-derived mAb, or with IgG from control patients. We found an increase in intrinsic excitability correlated with a reduction of the sensitivity to a selective Kv1.1-channel blocker in neurons treated with the LRR mAb, but not in neurons treated with the EPTP mAb. Our findings suggest LRR mAbs are able to modulate neuronal excitability that could account for epileptiform activity observed in patients. Autoantibodies directed against Leucine-rich Glioma-Inactivated protein 1 (LGI1) are found in patients with limbic encephalitis (LE) who have frequent focal seizures and hippocampal atrophy as hallmarks of their disease ,3. HyperMore recent reports aimed to better characterize the relative pathogenic roles of domain-specific antibodies by studying recombinant monoclonal LGI1 autoantibodies (mAb) derived from patient B cells ,8. mAbs In order to directly compare the electrophysiological effects of LRR- and EPTP-mAbs, we measured intrinsic excitability of CA3 neurons after their application. As LGI1 can alter the inactivation gating of the Kv1 channels , which tRat hippocampal slice cultures: All experiments were carried out according to the European and Institutional guidelines for the care and use of laboratory animals  and approved by the local health authority . Slice cultures were prepared as described previously [2–5% CO2. The culture medium contained 25 mL MEM, 12.5 mL HBSS, 12.5 mL horse serum, 0.5 mL penicillin/streptomycin, 0.8 mL glucose (1 M), 0.1 mL ascorbic acid (1 mg/mL), 0.4 mL Hepes (1 M), 0.5 mL B27, and 8.95 mL sterile H2O. To limit glial proliferation, 5 μM Ara-C was added to the culture medium starting at 4 d in vitro (DIV).eviously . In brieApplication of the mAbs: LGI1-specific recombinant mAbs were produced as described in Ramberger et al. 2020 [al. 2020 . Polycloal. 2020 ) and oneal. 2020 ) were asElectrophysiology: Whole-cell recordings were obtained from CA3 neurons in organotypic cultures at DIV7 and DIV8. Recordings were carried out in a limit of 6 h after the last application of the IgGs. The external solution contained: 125 mM NaCl, 26 mM NaHCO3, 3 mM CaCl2, 2.5 mM KCl, 2 mM MgCl2, 0.8 mM NaH2PO4, and 10 mM D-glucose, and was equilibrated with 95% O2–5% CO2. Patch pipettes (7–10 MΩ) were filled with a solution containing (mM): K-gluconate 120, KCl 20, Hepes 10, EGTA 0.5, MgCl2 2, Na2ATP 2, and NaGTP 0.3 (pH 7.4). Liquid junction potential (-12 mV) was not compensated. Organotypic cultures were quickly washed in the perfused recording chamber with the external solution by increasing the speed of perfusion pumps to facilitate the patch-clamp procedure. All recordings were made at 29 °C in a temperature-controlled recording chamber . CA3 pyramidal neurons were recorded in current clamp with a Multiclamp 700B Amplifier . Excitability was measured by delivering a range of long (1 s) depolarizing current pulses  and counting the number of action potentials  and the first spike latency , was determined by current-clamp recording before and after 5 min of bath application of DTx-K (100 nM). Acquisition was performed at 10 kHz with pClamp10 .Data were analyzed with ClampFit (Axon Instruments), LabView  and IgorPro . Pooled data are presented as mean ± SE and statistical analysis was performed using the Mann–Whitney U test or Wilcoxon rank signed test.n = 13 vs. LRR-mAb: 75.4 ± 7.5 pA n = 14, Mann-Whitney, p = 0.035; n = 13 vs. EPTP-mAb: 110.2 ± 15.6 pA n = 12, Mann-Whitney, p = 0.96; n = 13 in HC-IgG-treated neurons, −58.9 ± 1.8 mV, n = 14 in LRR-mAb-treated neurons, and −61.2 ± 1.5 mV, n = 12 in EPTP-mAb-treated neurons; Mann–Whitney, p = 0.94 and 0.29, respectively; input resistance: 226 ± 7 MΩ, n = 13 in HC-IgG-treated neurons vs. 222 ± 13 MΩ, n = 14 in LRR-mAb-treated neurons and 222 ± 14 MΩ, n = 12 in EPTP-mAb-treated neurons; Mann–Whitney, p = 0.45 and 0, 72; capacitance: 338 ± 14 pF n = 13 in HC-IgG-treated neurons vs. 330 ± 20 pF n = 14 in LRR-mAb-treated cells; Mann–Whitney, p = 0.68, and 353 ± 33 pF, n = 12 in EPTP-mAb-treated neurons; p = 0.89).To assess the effect of the two mAbs on neuronal excitability, we performed current-clamp recordings from CA3 pyramidal neurons in organotypic cultures of rat hippocampus treated with the different Abs. Input–output curves were established for each neuron A. A signn = 14 vs. 728 ± 43 ms n = 13, Mann–Whitney, p = 0.002; n = 13 vs. 762 ± 57 ms n = 12, Mann–Whitney, p = 0.34; n = 14 vs. 0.25 ± 0.03 mV/ms, n = 12; MW p < 0.001; n = 10 vs. 0.25 ± 0.03 mV/ms, n = 12; MW p = 0.4; n = 13 vs. −34.4 ± 0.8 mV in HC, n = 12; MW p = 0.18; Recordings of HC IgGs-treated neurons showed a characteristic ramp-and-delay profile preceding the evoked spike, strikingly observed at rheobase current A. This fn = 7, Wilcoxon, p = 0.016; n = 9, Wilcoxon, p = 0.009; n = 8, Wilcoxon, p = 0.035; Based on these findings, we asked whether changes in the D-type potassium current could account for the change in intrinsic excitability by measuring the sensitivity to DTx-k after LRR-mAb treatment. DTx-k strongly reduced the rheobase in HC IgG-treated neurons  and EPTP-mAbs  but not in LRR-mAbs  and EPTP-mAbs  but not in LRR-mAbs  [The increase in excitability observed in LRR-mAb-treated neurons is associated with a lower rheobase, a lower first spike latency, and an elevated depolarizing slope before the action potential. All these changes are mediated by Kv1.1 channels as the application of the selective Kv1.1 channel blocker, DTx-k had little effect on these parameters in LRR-mAb-treated neurons, but not in HC- and EPTP-mAb-treated neurons. The rheobase of LRR-mAb-treated neurons was slightly reduced in DTx-k, indicating that not all Kv1.1 channels are internalized by LRR-mAbs. Surprisingly, no significant change in action potential threshold was observed following treatment with LRR mAbs in our study. As the spike threshold depends on both voltage-gated sodium (Nav) and potassium channels, the lack of spike threshold change may be attributed to the homeostatic reduction of Nav channel density in LRR-mAb-treated neurons, as previously observed in over-excited neurons .Our results are compatible with previous studies showing that LRR-mAbs promote LGI1-ADAM complex internalization , which mAntibodies against LGI1 are known to prevent long-term synaptic potentiation (LTP) and memory formation in vivo ,8. InterThe molecular mechanism by which EPTP-mAbs mediate their effect is likely to occur through the prevention of LGI1 binding to its native receptors. As suggested in a recent study , EPTP-mA