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The purpose of the paper is to explore the relationships between geographical and virtual proximity in cluster organisations (COs). The authors report the findings from a qualitative study conducted in four COs in Poland. The basic technique for collecting and analysing data was an in-depth individual interview and qualitative content analysis. The research has shown that the relationships between geographical and virtual proximity depend on the cooperation level and the role of the CO. The findings presents a broader view on cluster cooperation as a phenomenon based on geographical proximity which facilitates personal interactions, but needs to be supported by various ICT tools.

Thin metallic Cu and Ni meshes were successfully embedded within SAC305 solder joints. Defects (residues) within the joint were removed by a vacuum step in the bonding sequence. The metallic mesh inlets were metallurgically bonded by the formation of scallop-like Cu6Sn5 and faceted Ni3Sn4 intermetallic compounds (IMCs) at the Cu mesh-SAC305 solder (CMS) and Ni mesh-SAC305 solder (NMS) interfaces, respectively. After process optimization, the averaged shear strengths were found to be 44.1 (reference), 44.7 (+1%), and 51.4 MPa (+16%) for SAC305, NMS, and CMS composite joints, respectively. The solder-substrate-mesh interaction resulted in a characteristic fracture pattern, with the cracking path partly within the solder and partly at the solder-mesh interface. Finite element (FE) simulations suggested a mesh-induced stiffening effect of the solder joint by 5%. The additional reinforcement (11%) introduced by the Cu mesh inlets was attributed to a locally enhanced fracture resistance. Keywords: Solder-mesh composite joints, Microstructure, Shear strength, Finite element modeling, Fracture

Requirements for electric vehicle (EV) propulsion systems—i.e., power density, switching frequency and cost—are becoming more stringent, while high reliability also needs to be ensured to maximize a vehicle’s life-cycle. Thus, the incorporation of a thermal management strategy is convenient, as most power inverter failure mechanisms are related to excessive semiconductor junction temperatures. This paper proposes a novel thermal management strategy which smartly varies the switching frequency to keep the semiconductors’ junction temperatures low enough and consequently extend the EV life-cycle. Thanks to the proposal, the drivetrain can operate safely at maximum attainable performance limits. The proposal is validated through simulation in an advanced digital platform, considering a 75-kW in-wheel Interior Permanent Magnet Synchronous Machine (IPMSM) drive fed by an automotive Silicon Carbide (SiC) power converter.

The evolution of the transient liquid-phase sintered (TLPS) Cu–Sn skeleton microstructure during thermal aging was evaluated to clarify the thermal reliability for die-attach applications. The Cu–Sn skeleton microstructure, which consists of Cu particles connected with Cu–Sn intermetallic compounds partially filled with polyimide resin, was obtained by the pressure-less TLP sintering process at 250 °C for 1 min using a novel Cu-solder-resin composite as a bonding material in a nitrogen atmosphere. Experimental results indicate that the TLPS joints were mainly composed of Cu, Cu6Sn5, and Cu3Sn in the as-bonded state, where submicron voids were observed at the interface between Cu3Sn and Cu particles. After thermal aging at 150, 175, and 200 °C for 1000 h, the Cu6Sn5 phase fully transformed into Cu3Sn except at the chip-side interface, where the number of the submicron voids appeared to increase. The averaged shear strengths were found to be 22.1 (reference), 22.8 (+3%), 24.0 (+9%), and 19.0 MPa (−14%) for the as-bonded state and specimens aged at 150, 175, and 200 °C for 1000 h, respectively. The TLPS joints maintained a shear strength over 19 MPa after thermal aging at 200 °C for 1000 h because of both the positive and negative impacts of the thermal aging, which include the transformation of Cu6Sn5 into Cu3Sn and the formation of submicron voids at the interface, respectively. These results indicate an excellent thermal reliability of the TLPS Cu–Sn skeleton microstructure.

Celem niniejszego artykułu jest próba zastosowania pojęcia „tożsamości” do analizy zjawisk i procesów związanych z powstawaniem i funkcjonowaniem klastrów oraz inicjatyw klastrowych. Struktury klastrowe stanowią formę grupy społecznej, dlatego winny podlegać tym samym tendencjom, pod których wpływem pozostają wszystkie inne grupy społeczne. Za jedną z takich najistotniejszych prawidłowości (bezpośrednio powiązanych z tożsamością) obserwowanych szczególnie wśród grup, których celem jest długie trwanie, uznać należy chęć wykształcenia mechanizmów – z jednej strony – wydzielających daną grupę i jej członków z otoczenia oraz – z drugiej – budujących wewnętrzną spójność i poczucie przywiązania uczestników danej struktury do siebie nawzajem i do struktury jako całości.

Celem artykułu jest stworzenie podwalin pod spójną koncepcję teoretyczną struktur klastrowych, spełniającą wysokie wymagania stale zmieniającego się pola nauk społecznych. Koncepcja taka winna dawać możliwość dokonywania porównań między klastrami różnych branż oraz będących na różnym etapie rozwoju. Do skonstruowania takiej teorii wykorzystano zmodyfikowaną i uzupełnioną koncepcję kapitałów Pierre’a Bourdieu, kładącą duży nacisk nie tylko na stricte ekonomiczne źródła oddziaływań w klastrze, lecz także na człowieka i jego działania, w największym stopniu wpływające na efektywne funkcjonowanie struktury klastrowej.

Abstract Therapeutics for traumatic brains injuries constitute a global unmet medical need. Despite the advances in neurocritical care, which have dramatically improved the survival rate for the ~ 70 million patients annually, few treatments have been developed to counter the long-term neuroinflammatory processes and accompanying cognitive impairments, frequent among patients. This review looks at gene delivery as a potential therapeutic development avenue for traumatic brain injury. We discuss the capacity of gene delivery to function in traumatic brain injury, by producing beneficial biologics within the brain. Gene delivery modalities, promising vectors and key delivery routes are discussed, along with the pathways that biological cargos could target to improve long-term outcomes for patients. Coupling blood-brain barrier crossing with sustained local production, gene delivery has the potential to convert proteins with useful biological properties, but poor pharmacodynamics, into effective therapeutics. Finally, we review the limitations and health economics of traumatic brain injury, and whether future gene delivery approaches will be viable for patients and health care systems.

Epidemiological delays are key quantities that inform public health policy and clinical practice. They are used as inputs for mathematical and statistical models, which in turn can guide control strategies. In recent work, we found that censoring, right truncation, and dynamical bias were rarely addressed correctly when estimating delays and that these biases were large enough to have knock-on impacts across a large number of use cases. Here, we formulate a checklist of best practices for estimating and reporting epidemiological delays. We also provide a flowchart to guide practitioners based on their data. Our examples are focused on the incubation period and serial interval due to their importance in outbreak response and modeling, but our recommendations are applicable to other delays. The recommendations, which are based on the literature and our experience estimating epidemiological delay distributions during outbreak responses, can help improve the robustness and utility of reported estimates and provide guidance for the evaluation of estimates for downstream use in transmission models or other analyses.

As a Principal Investigator leading a research team, creating a positive research culture for your team members is one of the best long-term investments you can make, for your research programme, for the sector and for society. A positive research environment is one where team members are empowered, recognised, have a clear career developmental pathway, can contribute to impactful and reproducible research and, ideally, propagate these effects. While these virtues can arise organically from a team built around kindness and integrity, they are also values that should be deliberately embedded within your lab. Here we provide advice on how to create a culture of integrity and a culture of belonging for your team members. We focus on thoughtful consideration of your key lab values, and the use of structure, language and your personal actions to make these values explicit. A holistic approach to integrating positive culture throughout every facet of your research team creates a system that can be self-sustaining in scientific integrity and more resilient to negative challenges. Starting on the pathway to self-improvement as a manager, recognising that this requires often uncomfortable self-reflection, provides both personal and professional reward.

Abstract Background Ageing is the principal risk factor for retinal degenerative diseases, which are the commonest cause of blindness in the developed countries. These conditions include age-related macular degeneration or diabetic retinopathy. Regulatory T cells play a vital role in immunoregulation of the nervous system by limiting inflammation and tissue damage in health and disease. Because the retina was long-considered an immunoprivileged site, the precise contribution of regulatory T cells in retinal homeostasis and in age-related retinal diseases remains unknown. Methods Regulatory T cells were selectively depleted in both young (2–4 months) and aged (18–23 months) FoxP3-DTR mice. We evaluated neuroretinal degeneration, gliosis, subretinal space phagocyte infiltration, and retinal pigmented epithelium morphology through immunofluorescence analysis. Subsequently, aged Treg depleted animals underwent adoptive transfer of both young and aged regulatory T cells from wild-type mice, and the resulting impact on neurodegeneration was assessed. Statistical analyses employed included the U-Mann Whitney test, and for comparisons involving more than two groups, 1-way ANOVA analysis followed by Bonferroni’s post hoc test. Results Our study shows that regulatory T cell elimination leads to retinal pigment epithelium cell dysmorphology and accumulation of phagocytes in the subretinal space of young and aged mice. However, only aged mice experience retinal neurodegeneration and gliosis. Surprisingly, adoptive transfer of young but not aged regulatory T cells reverse these changes. Conclusion Our findings demonstrate an essential role for regulatory T cells in maintaining age retinal homeostasis and preventing age-related neurodegeneration. This previously undescribed role of regulatory T cells in limiting retinal inflammation, RPE/choroid epithelium damage and subsequently photoreceptor loss with age, opens novel avenues to explore regulatory T cell neuroprotective and anti-inflammatory properties as potential therapeutic approaches for age-related retinal diseases.

Abstract Myelin regeneration (remyelination) is essential to prevent neurodegeneration in demyelinating diseases such as Multiple Sclerosis, however, its efficiency declines with age. Regulatory T cells (Treg) recently emerged as critical players in tissue regeneration, including remyelination. However, the effect of ageing on Treg-mediated regenerative processes is poorly understood. Here, we show that expansion of aged Treg does not rescue age-associated remyelination impairment due to an intrinsically diminished capacity of aged Treg to promote oligodendrocyte differentiation and myelination in male and female mice. This decline in regenerative Treg functions can be rescued by a young environment. We identified Melanoma Cell Adhesion Molecule 1 (MCAM1) and Integrin alpha 2 (ITGA2) as candidates of Treg-mediated oligodendrocyte differentiation that decrease with age. Our findings demonstrate that ageing limits the neuroregenerative capacity of Treg, likely limiting their remyelinating therapeutic potential in aged patients, and describe two mechanisms implicated in Treg-driven remyelination that may be targetable to overcome this limitation.

BackgroundWith the aging global population and the rising burden of Alzheimer disease and related dementias (ADRDs), there is a growing focus on identifying mild cognitive impairment (MCI) to enable timely interventions that could potentially slow down the onset of clinical dementia. The production of speech by an individual is a cognitively complex task that engages various cognitive domains. The ease of audio data collection highlights the potential cost-effectiveness and noninvasive nature of using human speech as a tool for cognitive assessment. ObjectiveThis study aimed to construct a machine learning pipeline that incorporates speaker diarization, feature extraction, feature selection, and classification to identify a set of acoustic features derived from voice recordings that exhibit strong MCI detection capability. MethodsThe study included 100 MCI cases and 100 cognitively normal controls matched for age, sex, and education from the Framingham Heart Study. Participants' spoken responses on neuropsychological tests were recorded, and the recorded audio was processed to identify segments of each participant's voice from recordings that included voices of both testers and participants. A comprehensive set of 6385 acoustic features was then extracted from these voice segments using OpenSMILE and Praat software. Subsequently, a random forest model was constructed to classify cognitive status using the features that exhibited significant differences between the MCI and cognitively normal groups. The MCI detection performance of various audio lengths was further examined. ResultsAn optimal subset of 29 features was identified that resulted in an area under the receiver operating characteristic curve of 0.87, with a 95% CI of 0.81-0.94. The most important acoustic feature for MCI classification was the number of filled pauses (importance score=0.09, P=3.10E–08). There was no substantial difference in the performance of the model trained on the acoustic features derived from different lengths of voice recordings. ConclusionsThis study showcases the potential of monitoring changes to nonsemantic and acoustic features of speech as a way of early ADRD detection and motivates future opportunities for using human speech as a measure of brain health.

As a Principal Investigator leading a research team, creating a positive research culture for your team members is one of the best long-term investments you can make, for your research programme, for the sector and for society. A positive research environment is one where team members are empowered, recognised, have a clear career developmental pathway, can contribute to impactful and reproducible research and, ideally, propagate these effects. While these virtues can arise organically from a team built around kindness and integrity, they are also values that should be deliberately embedded within your lab. Here we provide advice on how to create a culture of integrity and a culture of belonging for your team members. We focus on thoughtful consideration of your key lab values, and the use of structure, language and your personal actions to make these values explicit. A holistic approach to integrating positive culture throughout every facet of your research team creates a system that can be self-sustaining in scientific integrity and more resilient to negative challenges. Starting on the pathway to self-improvement as a manager, recognising that this requires often uncomfortable self-reflection, provides both personal and professional reward.

Microbiome research has gained much attention in recent years as the importance of gut microbiota in regulating host health becomes increasingly evident. However, the impact of radiation on the microbiota in the murine bone marrow transplantation model is still poorly understood. In this paper, we present key findings from our study on how radiation, followed by bone marrow transplantation with or without T cell depletion, impacts the microbiota in the ileum and caecum. Our findings show that radiation has different effects on the microbiota of the two intestinal regions, with the caecum showing increased interindividual variation, suggesting an impaired ability of the host to regulate microbial symbionts, consistent with the Anna Karenina principle. Additionally, we observed changes in the ileum composition, including an increase in bacterial taxa that are important modulators of host health, such as Akkermansia and Faecalibaculum. In contrast, radiation in the caecum was associated with an increased abundance of several common commensal taxa in the gut, including Lachnospiraceae and Bacteroides. Finally, we found that high doses of radiation had more substantial effects on the caecal microbiota of the T-cell-depleted group than that of the non-T-cell-depleted group. Overall, our results contribute to a better understanding of the complex relationship between radiation and the gut microbiota in the context of bone marrow transplantation and highlight the importance of considering different intestinal regions when studying microbiome responses to environmental stressors.

Recently, OTULIN haploinsufficiency was linked to enhanced susceptibility to Staphylococcus aureus infections accompanied by local necrosis and systemic inflammation. The pathogenesis observed in haploinsufficient patients differs from the hyperinflammation seen in classical OTULIN-related autoinflammatory syndrome (ORAS) patients and is characterized by increased susceptibility of dermal fibroblasts to S. aureus alpha toxin-inflicted cytotoxic damage. Immunological abnormalities were not observed in OTULIN haploinsufficient patients, suggesting a non-hematopoietic basis. In this research report, we investigated an Otulin+/− mouse model after in vivo provocation with lipopolysaccharide (LPS) to explore the potential role of hematopoietic-driven inflammation in OTULIN haploinsufficiency. We observed a hyperinflammatory signature in LPS-provoked Otulin+/− mice, which was driven by CD64+ monocytes and macrophages. Bone marrow-derived macrophages (BMDMs) of Otulin+/− mice demonstrated higher proinflammatory cytokine secretion after in vitro stimulation with LPS or polyinosinic:polycytidylic acid (Poly(I:C)). Our experiments in full and mixed bone marrow chimeric mice suggest that, in contrast to humans, the observed inflammation was mainly driven by the hematopoietic compartment with cell-extrinsic effects likely contributing to inflammatory outcomes. Using an OTULIN haploinsufficient mouse model, we validated the role of OTULIN in the regulation of environmentally directed inflammation.

The time-varying effective reproduction number Rt is a widely used indicator of transmission dynamics during infectious disease outbreaks. Timely estimates of Rt can be obtained from reported cases counted by their date of symptom onset, which is generally closer to the time of infection than the date of report. Case counts by date of symptom onset are typically obtained from line list data, however these data can have missing information and are subject to right truncation. Previous methods have addressed these problems independently by first imputing missing onset dates, then adjusting truncated case counts, and finally estimating the effective reproduction number. This stepwise approach makes it difficult to propagate uncertainty and can introduce subtle biases during real-time estimation due to the continued impact of assumptions made in previous steps. In this work, we integrate imputation, truncation adjustment, and Rt estimation into a single generative Bayesian model, allowing direct joint inference of case counts and Rt from line list data with missing symptom onset dates. We then use this framework to compare the performance of nowcasting approaches with different stepwise and generative components on synthetic line list data for multiple outbreak scenarios and across different epidemic phases. We find that under reporting delays realistic for hospitalization data (50% of reports delayed by more than a week), intermediate smoothing, as is common practice in stepwise approaches, can bias nowcasts of case counts and Rt, which is avoided in a joint generative approach due to shared regularization of all model components. On incomplete line list data, a fully generative approach enables the quantification of uncertainty due to missing onset dates without the need for an initial multiple imputation step. In a real-world comparison using hospitalization line list data from the COVID-19 pandemic in Switzerland, we observe the same qualitative differences between approaches. The generative modeling components developed in this work have been integrated and further extended in the R package epinowcast, providing a flexible and interpretable tool for real-time surveillance.

Abstract Background Accurate estimation of the effective reproductive number ( $$R_e$$ R e ) of epidemic outbreaks is of central relevance to public health policy and decision making. We present estimateR, an R package for the estimation of the reproductive number through time from delayed observations of infection events. Such delayed observations include confirmed cases, hospitalizations or deaths. The package implements the methodology of Huisman et al. but modularizes the $$R_e$$ R e estimation procedure to allow easy implementation of new alternatives to the currently available methods. Users can tailor their analyses according to their particular use case by choosing among implemented options. Results The estimateR R package allows users to estimate the effective reproductive number of an epidemic outbreak based on observed cases, hospitalization, death or any other type of event documenting past infections, in a fast and timely fashion. We validated the implementation with a simulation study: estimateR yielded estimates comparable to alternative publicly available methods while being around two orders of magnitude faster. We then applied estimateR to empirical case-confirmation incidence data for COVID-19 in nine countries and for dengue fever in Brazil; in parallel, estimateR is already being applied (i) to SARS-CoV-2 measurements in wastewater data and (ii) to study influenza transmission based on wastewater and clinical data in other studies. In summary, this R package provides a fast and flexible implementation to estimate the effective reproductive number for various diseases and datasets. Conclusions The estimateR R package is a modular and extendable tool designed for outbreak surveillance and retrospective outbreak investigation. It extends the method developed for COVID-19 by Huisman et al. and makes it available for a variety of pathogens, outbreak scenarios, and observation types. Estimates obtained with estimateR can be interpreted directly or used to inform more complex epidemic models (e.g. for forecasting) on the value of $$R_e$$ R e .