Approximately 25% of the

BACKGROUND Estimates for the prevalence of food allergy vary widely, with a paucity of data for adults. The aim of this analysis was to report trends in the incidence and prevalence of food allergy in England, using a national primary care dataset. METHODS We analysed data from Clinical Practice Research Datalink between 1998 and 2018, with linked data to relevant hospital encounters in England. The main outcomes were incidence and prevalence of food allergy, according to three definitions of food allergy: possible food allergy, probable food allergy, and probable food allergy with adrenaline autoinjectors prescription. We also evaluated the difference in proportion of patients prescribed adrenaline autoinjectors by English Index of Multiple Deprivation (IMD), age, and by previous food anaphylaxis, and explored differences in patient encounters (general practice vs emergency department setting). FINDINGS 7 627 607 individuals in the dataset were eligible for inclusion, of whom 150 018 (median age 19 years [IQR 4-34]; 82 614 [55·1%] female and 67 404 [44·9%] male) had a possible food allergy. 121 706 met diagnostic criteria for probable food allergy, of whom 38 288 were prescribed adrenaline autoinjectors. Estimated incidence of probable food allergy doubled between 2008 and 2018, from 75·8 individuals per 100 000 person-years (95% CI 73·7-77·9) in 2008 to 159·5 (156·6-162·3) individuals per 100 000 person-years in 2018. Prevalence increased from 0·4% (23 399 of 6 432 383) to 1·1% (82 262 of 7 627 607) over the same period and was highest in children under 5 years (11 951 [4·0%] of 296 406 in 2018) with lower prevalence in school-aged children (from 11 353 [2·4%] of 473 597 in 2018 for children aged 5-9 years to 6896 [1·7%] of 404 525 for those aged 15-19 years) and adults (42 848 [0·7%] of 5 992 454 in 2018). In those with previous food anaphylaxis, only 2321 (58·3%) of 3980 (975 [64·0%] of 1524 children and young people and 1346 [54·8%] of 2456 adults) had a prescription for adrenaline autoinjector. Adrenaline autoinjectors prescription was less common in those resident in more deprived areas (according to IMD). In the analysis of health-care encounters, 488 604 (97·1%) of 503 198 visits recorded for food allergy occurred in primary care, with 115 655 (88·4%) of 130 832 patients managed exclusively in primary care. INTERPRETATION These estimates indicate an important and increasing burden of food allergy in England. Our findings that most patients with food allergy are managed outside the hospital system, with low rates of adrenaline autoinjector prescription in those with previous anaphylaxis, highlight a need to better support those working in primary care to ensure optimal management of patients with food allergy. FUNDING UK Food Standards Agency and UK Medical Research Council.

African swine fever virus (ASFV) has been spreading through Europe, Asia, and the Caribbean after its introduction in Georgia in 2007 and, due to its particularly high mortality rate, poses a continuous threat to the pig industry. The golden standard to trace back the ASFV is whole genome sequencing, but it is a cost and time-intensive methodology. A more efficient way of tracing the virus is to amplify only specific genomic regions relevant for genotyping. This is mainly accomplished by amplifying single amplicons by PCR followed by Sanger sequencing. To reduce costs and processivity time, we evaluated a multiplex PCR based on the four primer sets routinely used for ASFV genotyping (B646L, E183L, B602L, and intergenic I73R-I329L), which was followed by Nanopore ligation-based amplicon sequencing. We show that with this protocol, we can genotype ASFV DNA originating from different biological matrices and correctly classify multiple genotypes and strains using a single PCR reaction. Further optimization of this method can be accomplished by adding or swapping the primer sets used for amplification based on the needs of a specific country or region, making it a versatile tool that can speed up the processing time and lower the costs of genotyping during ASFV outbreaks.

Background Pharmacological treatment options for patients with dementia owing to Alzheimer's disease are limited to symptomatic therapy. Recently, the US Food and Drug Administration approved the monoclonal antibody lecanemab for the treatment of amyloid-positive patients with mild cognitive impairment (MCI) and early Alzheimer´s dementia. European approval is expected in 2024. Data on the applicability and eligibility for treatment with anti-amyloid monoclonal antibodies outside of a study population are lacking. Aims This study examined eligibility criteria for lecanemab in a real-world memory clinic population between 1 January 2022 and 31 July 2023. Method We conducted a retrospective, single-centre study applying the clinical trial eligibility criteria for lecanemab to out-patients of a specialised psychiatric memory clinic. Eligibility for anti-amyloid treatment was assessed following the phase 3 inclusion and exclusion criteria and the published recommendations for lecanemab. Results The study population consisted of 587 out-patients. Two-thirds were diagnosed with Alzheimer's disease (probable or possible Alzheimer's disease dementia in 43.6% of cases, n = 256) or MCI (23%, n = 135), and 33.4% (n = 196) were diagnosed with dementia or neurocognitive disorder owing to another aetiology. Applying all lecanemab eligibility criteria, 11 (4.3%) patients with dementia and two (1.5%) patients with MCI would have been eligible for treatment with this compound, whereas 13 dementia (5.1%) and 14 (10.4%) MCI patients met clinical inclusion criteria, but had no available amyloid status. Conclusions Even in a memory clinic with a good infrastructure and sufficient facilities for dementia diagnostics, most patients do not meet the eligibility criteria for treatment with lecanemab.

The Sustainable Development Goals are far off track. The convergence of global threats such as climate change, conflict and the lasting effects of the COVID-19 pandemic—among others—call for better data and research evidence that can account for the complex interactions between these threats. In the time of polycrisis, global and national-level data and research evidence must address complexity. Viewed through the lens of ‘systemic risk’, there is a need for data and research evidence that is sufficiently representative of the multiple interdependencies of global threats. Instead, current global published literature seems to be dominated by correlational, descriptive studies that are unable to account for complex interactions. The literature is geographically limited and rarely from countries facing severe polycrisis threats. As a result, country guidance fails to treat these threats interdependently. Applied systems thinking can offer more diverse research methods that are able to generate complex evidence. This is achievable through more participatory processes that will assist stakeholders in defining system boundaries and behaviours. Additionally, applied systems thinking can draw on known methods for hypothesising, modelling, visualising and testing complex system properties over time. Application is much needed for generating evidence at the global level and within national-level policy processes and structures.

Objective To evaluate the systemic immune-inflammation (SII) index in patients with rheumatoid arthritis (RA) stratified by systemic inflammatory status. Methods Seropositive patients with RA (n=58) were divided into two groups based on serum hs-C-reactive protein (hs-CRP) levels: RA patients with hs-CRP levels of at or 3 mg/L or above (high systemic inflammatory status; n=38) and RA patients with hs-CRP levels of less than 3 mg/L (low systemic inflammatory status; n=20). The control group comprised 31 healthy individuals. Blood samples were tested for the next parameters: leukocytes, neutrophilic granulocytes, lymphocytes, thrombocytes [platelet (PLT)], high-sensitivity hs-CRP, sed rate [erythrocyte sedimentation rate (ESR)], neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR). The SII index was derived as Neu x PLT/Lym. Results In patients with RA, the SII index was elevated compared with that of healthy individuals and positively correlated with hs-CRP, erythrocyte sedimentation rate, NLR, MLR, PLR, tender joint count, and swollen-to-tender joint count ratio. Patients with RA who had hs-CRP levels of 3 mg/L above exhibited a statistically significant increase in the SII compared with those with hs-CRP levels below 3 mg/L. Additionally, within the cohort of RA patients with hs-CRP levels at or above 3 mg/L, a positive correlation was found between the SII index and both NLR and PLR. The SII index was positively correlated with NLR, MLR, and PLR in RA patients with hs-CRP levels below 3 mg/L. The cut-off point of the SII index for distinguishing between RA cases with hs-CRP levels 3 mg/L and those with hs-CRP levels 3 mg/L or higher was ≥323.4, with a sensitivity of 77.6% and a specificity of 54.8%. Conclusions The serum SII index can be a potentially useful marker for evaluating the inflammatory process and clinical progression of RA.

Background Introduction: Vitamin D plays significant role in calcium metabolism and in bone and vascular calcifications. Objective: To investigate the association between vitamin D level, arterial hypertension, arterial stiffness and coronary calcifications detected by MSCT. Method: A 2 female case report comparative to each other investigated the correlation between vitamin D serum level, blood pressure, arterial stiffness and severity of the coronary calcification using MSCT diagnostic tool estimating the calcium score. Results: The first case report showed that decreased level of vitamin D is correlated with increased blood pressure, increased arterial stiffness and with a severe coronary calcifications. The second case report showed normal blood pressure, normal vascular age and low calcium score in a no-defficient vitamin D female. Conclusion: Vitamin D has impact on blood pressure, arterial stiffness, coronary calcifications and coronary heart disease. The lower vitamin D, the higher arterial blood pressure, arterial stiffness and coronary calcium score.

CONTEXT Immune-oncology strategies are revolutionising the perioperative treatment in several tumour types. The perioperative setting of renal cell carcinoma (RCC) is an evolving field, and the advent of immunotherapy is producing significant advances. OBJECTIVE To critically review the potential pros and cons of adjuvant and neoadjuvant immune-based therapeutic strategies in RCC, and to provide insights for future research in this field. EVIDENCE ACQUISITION We performed a collaborative narrative review of the existing literature. EVIDENCE SYNTHESIS Adjuvant immunotherapy with pembrolizumab is a new standard of care for patients at a higher risk of recurrence after nephrectomy, demonstrating a disease-free survival and overall survival benefit in the phase 3 KEYNOTE-564 trial. Current data do not support neoadjuvant therapy use outside clinical trials. While both adjuvant and neoadjuvant immune-based approaches are driven by robust biological rationale, neoadjuvant immunotherapy may enable a stronger and more durable antitumour immune response. If neoadjuvant single-agent immune checkpoint inhibitors demonstrated limited activity on the primary tumour, immune-based combinations may show increased activity. Overtreatment and a risk of relevant toxicity for patients who are cured by surgery alone are common concerns for both neoadjuvant and adjuvant strategies. Biomarkers helping patient selection and treatment deintensification are lacking in RCC. No results from randomised trials comparing neoadjuvant or perioperative immune-based therapy with adjuvant immunotherapy are available. CONCLUSIONS Adjuvant immunotherapy is a new standard of care in RCC. Both neoadjuvant and adjuvant immunotherapy strategies have potential advantages and disadvantages. Optimising perioperative treatment strategies is nuanced, with the role of neoadjuvant immune-based therapies yet to be defined. Given strong biological rationale for a pre/perioperative approach, there is a need for prospective clinical trials to determine clinical efficacy. Research investigating biomarkers aiding patient selection and treatment deintensification strategies is needed. PATIENT SUMMARY Immunotherapy is transforming the treatment of kidney cancer. In this review, we looked at the studies investigating immunotherapy strategies before and/or after surgery for patients with kidney cancer to assess potential pros and cons. We concluded that both neoadjuvant and adjuvant immunotherapy strategies may have potential advantages and disadvantages. While immunotherapy administered after surgery is already a standard of care, immunotherapy before surgery should be better investigated in future studies. Future trials should also focus on the selection of patients in order to spare toxicity for patients who will be cured by surgery alone.

In recent advancements in robotics, Artificial Intelligence (AI) methods such as Deep Learning, Deep Reinforcement Learning (DRL), Transformers, and Large Language Models (LLMs) have significantly enhanced robotic capabilities. Key AI models driving advancements in robotic vision include Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), the DEtection Transformers (DETR), the YOLO family of algorithms, segmentation techniques, and 3D vision technologies. Deep Reinforcement Learning (DRL), an AI technique where agents learn optimal behaviors through trial and error interactions with their environment, enables robots to perform complex tasks autonomously. Transformers, originally developed for natural language processing, have been adapted to robotics for tasks involving sequence prediction and data understanding, improving perception and decision-making processes. LLMs leverage vast amounts of text data to enhance robot-human interaction, enabling robots to understand and generate human-like language, thus improving their communicative and collaborative abilities in various applications. The integration of these AI methods enhances the adaptability, efficiency, and overall performance of robotic systems, paving the way for more sophisticated and intelligent autonomous agents.

In the last ten years, the development and research of advanced technologies, as well as their application in all segments of society, have led to major changes and reshaping of the new world. New innovations are occurring on a daily basis, but their application is not going fast enough due to the rigid infrastructure. However, in order to secure an optimal future, we all have to adapt to the changes that are coming. The developed countries have adopted the strict implementation of advanced technologies of Industry 4.0, some of which include: Internet of Things (IoT), Big Data, Cloud Computing, smart sensors, Radio Frequency Identification (RFID), 3D printing, advanced security systems, Virtual and Augmented Reality (VAR), etc. Robotics is the basic and first technology that has been implemented since the 60s of the last century, with artificial intelligence coming in the spotlight in the last ten years. Artificial intelligence is becoming a key to the development of advanced robots, as it enables them to adapt to unpredictable situations, to learn from experience and make intelligent decisions.Robots use AI to process sensor data, navigate, recognize objects, plan paths and interact with the environment. In short, artificial intelligence enables robots to be smart, whereas robotics uses AI to create autonomous and useful devices. This symbiosis contributes to progress in many industries, including healthcare, manufacturing and transportation. Artificial intelligence (AI) and robotics are two key fields that complement each other. The paper presents the trend of applied and approved patents in artificial intelligence and robotics, as well as an example of the use of artificial intelligence in advanced robots to perform certain tasks. Artificial intelligence (AI) is having an increasing impact on robotics, opening up many possibilities.

U radu je predstavljen postupak izbora najpogodnijeg numeričkog modela za utvrđivanje indeksa staništa (SI – site index) kao apsolutne mjere proizvodnog potencijala (boniteta) staništa jednodobnih nenjegovanih sastojina bijelog bora na karbonatnim supstratima u BiH. Objekat istraživanja su predstavljale jednodobne nenjegovane sastojine bijelog bora različitih taksacionih i stanišnih karakteristika. Metodom privremenih oglednih parcela prikupljeno je više općih i taksacionih podataka, a zatim su njihovom obradom i analizom utvrđeni najvažniji strukturni i proizvodni parametri sastojina odvojeno po relativnim visinskim bonitetnim klasama staništa (RB). Za utvrđivanje numeričkog modela za procjenu indeksa staništa (SI) primijenjene su metode korelacione i regresione analize, a za predstavljanje veličina osnovnih taksacionih elemenata prema veličinama SI grafička metoda. U cilju predstavljanja veličina osnovnih taksacionih elemenata po utvrđenim SI klasama uspostavljena je korelaciona veza između SI50 (pri starosti od 50 godina)i postojećih relativnih bonitetnih klasa (RB) jednodobnih sastojina bijelog bora. Ova veza je poslužila za izradu proizvodne diferencijacije staništa jednodobnih sastojina bijelog bora na karbonatnim susptratima u BiH koja omogućava prikaz veličina osnovnih taksacionih elemenata ovih sastojina zavisno od starosti i SI50. Poređenjem utvrđenih rezultata istraživanja s odgovarajućim rezultatima drugih autora zaključeno je da su jednodobne sastojine bijelog bora u BiH srednje produktivne.