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Nick K. Jones1,2*, Lucy Rivett1,2*, Chris Workman3, Mark Ferris3, Ashley Shaw1, Cambridge COVID-19 Collaboration1,4, Paul J. Lehner1,4, Rob Howes5, Giles Wright3, Nicholas J. Matheson1,4,6¶, Michael P. Weekes1,7¶1 Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK2 Clinical Microbiology & Public Health Laboratory, Public Health England, Cambridge, UK3 Occupational Health and Wellbeing, Cambridge Biomedical Campus, Cambridge, UK4 Cambridge Institute of Therapeutic Immunology & Infectious Disease, University of Cambridge, Cambridge, UK5 Cambridge COVID-19 Testing Centre and AstraZeneca, Anne Mclaren Building, Cambridge, UK6 NHS Blood and Transplant, Cambridge, UK7 Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK*Joint first authorship¶Joint last authorshipCorrespondence: mpw1001@cam.ac.ukThe UK has initiated mass COVID-19 immunisation, with healthcare workers (HCWs) given early priority because of the potential for workplace exposure and risk of onward transmission to patients. The UK’s Joint Committee on Vaccination and Immunisation has recommended maximising the number of people vaccinated with first doses at the expense of early booster vaccinations, based on single dose efficacy against symptomatic COVID-19 disease.1-3At the time of writing, three COVID-19 vaccines have been granted emergency use authorisation in the UK, including the BNT162b2 mRNA COVID-19 vaccine (Pfizer-BioNTech). A vital outstanding question is whether this vaccine prevents or promotes asymptomatic SARS-CoV-2 infection, rather than symptomatic COVID-19 disease, because sub-clinical infection following vaccination could continue to drive transmission. This is especially important because many UK HCWs have received this vaccine, and nosocomial COVID-19 infection has been a persistent problem.Through the implementation of a 24 h-turnaround PCR-based comprehensive HCW screening programme at Cambridge University Hospitals NHS Foundation Trust (CUHNFT), we previously demonstrated the frequent presence of pauci- and asymptomatic infection amongst HCWs during the UK’s first wave of the COVID-19 pandemic.4 Here, we evaluate the effect of first-dose BNT162b2 vaccination on test positivity rates and cycle threshold (Ct) values in the asymptomatic arm of our programme, which now offers weekly screening to all staff.Vaccination of HCWs at CUHNFT began on 8th December 2020, with mass vaccination from 8th January 2021. Here, we analyse data from the two weeks spanning 18thto 31st January 2021, during which: (a) the prevalence of COVID-19 amongst HCWs remained approximately constant; and (b) we screened comparable numbers of vaccinated and unvaccinated HCWs. Over this period, 4,408 (week 1) and 4,411 (week 2) PCR tests were performed from individuals reporting well to work. We stratified HCWs <12 days or > 12 days post-vaccination because this was the point at which protection against symptomatic infection began to appear in phase III clinical trial.226/3,252 (0·80%) tests from unvaccinated HCWs were positive (Ct<36), compared to 13/3,535 (0·37%) from HCWs <12 days post-vaccination and 4/1,989 (0·20%) tests from HCWs ≥12 days post-vaccination (p=0·023 and p=0·004, respectively; Fisher’s exact test, Figure). This suggests a four-fold decrease in the risk of asymptomatic SARS-CoV-2 infection amongst HCWs ≥12 days post-vaccination, compared to unvaccinated HCWs, with an intermediate effect amongst HCWs <12 days post-vaccination.A marked reduction in infections was also seen when analyses were repeated with: (a) inclusion of HCWs testing positive through both the symptomatic and asymptomatic arms of the programme (56/3,282 (1·71%) unvaccinated vs 8/1,997 (0·40%) ≥12 days post-vaccination, 4·3-fold reduction, p=0·00001); (b) inclusion of PCR tests which were positive at the limit of detection (Ct>36, 42/3,268 (1·29%) vs 15/2,000 (0·75%), 1·7-fold reduction, p=0·075); and (c) extension of the period of analysis to include six weeks from December 28th to February 7th 2021 (113/14,083 (0·80%) vs 5/4,872 (0·10%), 7·8-fold reduction, p=1x10-9). In addition, the median Ct value of positive tests showed a non-significant trend towards increase between unvaccinated HCWs and HCWs > 12 days post-vaccination (23·3 to 30·3, Figure), suggesting that samples from vaccinated individuals had lower viral loads.We therefore provide real-world evidence for a high level of protection against asymptomatic SARS-CoV-2 infection after a single dose of BNT162b2 vaccine, at a time of predominant transmission of the UK COVID-19 variant of concern 202012/01 (lineage B.1.1.7), and amongst a population with a relatively low frequency of prior infection (7.2% antibody positive).5This work was funded by a Wellcome Senior Clinical Research Fellowship to MPW (108070/Z/15/Z), a Wellcome Principal Research Fellowship to PJL (210688/Z/18/Z), and an MRC Clinician Scientist Fellowship (MR/P008801/1) and NHSBT workpackage (WPA15-02) to NJM. Funding was also received from Addenbrooke’s Charitable Trust and the Cambridge Biomedical Research Centre. We also acknowledge contributions from all staff at CUHNFT Occupational Health and Wellbeing and the Cambridge COVID-19 Testing Centre.

Scene flow tracks the three-dimensional (3D) motion of each point in adjacent point clouds. It provides fundamental 3D motion perception for autonomous driving and server robot. Although the Red Green Blue Depth (RGBD) camera or Light Detection and Ranging (LiDAR) capture discrete 3D points in space, the objects and motions usually are continuous in the macro world. That is, the objects keep themselves consistent as they flow from the current frame to the next frame. Based on this insight, the Generative Adversarial Networks (GAN) is utilized to self-learn 3D scene flow with no need for ground truth. The fake point cloud of the second frame is synthesized from the predicted scene flow and the point cloud of the first frame. The adversarial training of the generator and discriminator is realized through synthesizing indistinguishable fake point cloud and discriminating the real point cloud and the synthesized fake point cloud. The experiments on Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) scene flow dataset show that our method realizes promising results without ground truth. Just as human, the proposed method can identify the similar local structures of two adjacent frames even without knowing the ground truth scene flow. Then, the local correspondence can be correctly estimated, and further the scene flow is correctly estimated.   Corresponding author(s) Email: wanghesheng@sjtu.edu.cn

Leukocyte differential test is a widely performed clinical procedure for screening infectious diseases. Existing hematology analyzers require labor-intensive work and a panel of expensive reagents. Here we report an artificial-intelligence enabled reagent-free imaging hematology analyzer (AIRFIHA) modality that can accurately classify subpopulations of leukocytes with minimal sample preparation. AIRFIHA is realized through training a two-step residual neural network using label-free images of isolated leukocytes acquired from a custom-built quantitative phase microscope. By leveraging the rich information contained in quantitative phase images, we not only achieved high accuracy in differentiating B and T lymphocytes, but also classified CD4 and CD8 cells, therefore outperforming the classification accuracy of most current hematology analyzers. We validated the performance of AIRFIHA in a randomly selected test set and cross-validated it across all blood donors. Owing to its easy operation, low cost, and accurate discerning capability of complex leukocyte subpopulations, we envision AIRFIHA is clinically translatable and can also be deployed in resource-limited settings, e.g., during pandemic situations for the rapid screening of infectious diseases.  Corresponding author(s) Email:    rjzhou@cuhk.edu.hk,  rishikesh.pandey@uconn.edu

Tam Hunt [1], Jonathan SchoolerUniversity of California Santa Barbara Synchronization, harmonization, vibrations, or simply resonance in its most general sense seems to have an integral relationship with consciousness itself. One of the possible “neural correlates of consciousness” in mammalian brains is a combination of gamma, beta and theta synchrony. More broadly, we see similar kinds of resonance patterns in living and non-living structures of many types. What clues can resonance provide about the nature of consciousness more generally? This paper provides an overview of resonating structures in the fields of neuroscience, biology and physics and attempts to coalesce these data into a solution to what we see as the “easy part” of the Hard Problem, which is generally known as the “combination problem” or the “binding problem.” The combination problem asks: how do micro-conscious entities combine into a higher-level macro-consciousness? The proposed solution in the context of mammalian consciousness suggests that a shared resonance is what allows different parts of the brain to achieve a phase transition in the speed and bandwidth of information flows between the constituent parts. This phase transition allows for richer varieties of consciousness to arise, with the character and content of that consciousness in each moment determined by the particular set of constituent neurons. We also offer more general insights into the ontology of consciousness and suggest that consciousness manifests as a relatively smooth continuum of increasing richness in all physical processes, distinguishing our view from emergentist materialism. We refer to this approach as a (general) resonance theory of consciousness and offer some responses to Chalmers’ questions about the different kinds of “combination problem.”  At the heart of the universe is a steady, insistent beat: the sound of cycles in sync…. [T]hese feats of synchrony occur spontaneously, almost as if nature has an eerie yearning for order. Steven Strogatz, Sync: How Order Emerges From Chaos in the Universe, Nature and Daily Life (2003) If you want to find the secrets of the universe, think in terms of energy, frequency and vibration.Nikola Tesla (1942) I.               Introduction Is there an “easy part” and a “hard part” to the Hard Problem of consciousness? In this paper, we suggest that there is. The harder part is arriving at a philosophical position with respect to the relationship of matter and mind. This paper is about the “easy part” of the Hard Problem but we address the “hard part” briefly in this introduction.  We have both arrived, after much deliberation, at the position of panpsychism or panexperientialism (all matter has at least some associated mind/experience and vice versa). This is the view that all things and processes have both mental and physical aspects. Matter and mind are two sides of the same coin.  Panpsychism is one of many possible approaches that addresses the “hard part” of the Hard Problem. We adopt this position for all the reasons various authors have listed (Chalmers 1996, Griffin 1997, Hunt 2011, Goff 2017). This first step is particularly powerful if we adopt the Whiteheadian version of panpsychism (Whitehead 1929).  Reaching a position on this fundamental question of how mind relates to matter must be based on a “weight of plausibility” approach, rather than on definitive evidence, because establishing definitive evidence with respect to the presence of mind/experience is difficult. We must generally rely on examining various “behavioral correlates of consciousness” in judging whether entities other than ourselves are conscious – even with respect to other humans—since the only consciousness we can know with certainty is our own. Positing that matter and mind are two sides of the same coin explains the problem of consciousness insofar as it avoids the problems of emergence because under this approach consciousness doesn’t emerge. Consciousness is, rather, always present, at some level, even in the simplest of processes, but it “complexifies” as matter complexifies, and vice versa. Consciousness starts very simple and becomes more complex and rich under the right conditions, which in our proposed framework rely on resonance mechanisms. Matter and mind are two sides of the coin. Neither is primary; they are coequal.  We acknowledge the challenges of adopting this perspective, but encourage readers to consider the many compelling reasons to consider it that are reviewed elsewhere (Chalmers 1996, Griffin 1998, Hunt 2011, Goff 2017, Schooler, Schooler, & Hunt, 2011; Schooler, 2015).  Taking a position on the overarching ontology is the first step in addressing the Hard Problem. But this leads to the related questions: at what level of organization does consciousness reside in any particular process? Is a rock conscious? A chair? An ant? A bacterium? Or are only the smaller constituents, such as atoms or molecules, of these entities conscious? And if there is some degree of consciousness even in atoms and molecules, as panpsychism suggests (albeit of a very rudimentary nature, an important point to remember), how do these micro-conscious entities combine into the higher-level and obvious consciousness we witness in entities like humans and other mammals?  This set of questions is known as the “combination problem,” another now-classic problem in the philosophy of mind, and is what we describe here as the “easy part” of the Hard Problem. Our characterization of this part of the problem as “easy”[2] is, of course, more than a little tongue in cheek. The authors have discussed frequently with each other what part of the Hard Problem should be labeled the easier part and which the harder part. Regardless of the labels we choose, however, this paper focuses on our suggested solution to the combination problem.  Various solutions to the combination problem have been proposed but none have gained widespread acceptance. This paper further elaborates a proposed solution to the combination problem that we first described in Hunt 2011 and Schooler, Hunt, and Schooler 2011. The proposed solution rests on the idea of resonance, a shared vibratory frequency, which can also be called synchrony or field coherence. We will generally use resonance and “sync,” short for synchrony, interchangeably in this paper. We describe the approach as a general resonance theory of consciousness or just “general resonance theory” (GRT). GRT is a field theory of consciousness wherein the various specific fields associated with matter and energy are the seat of conscious awareness.  A summary of our approach appears in Appendix 1.  All things in our universe are constantly in motion, in process. Even objects that appear to be stationary are in fact vibrating, oscillating, resonating, at specific frequencies. So all things are actually processes. Resonance is a specific type of motion, characterized by synchronized oscillation between two states.  An interesting phenomenon occurs when different vibrating processes come into proximity: they will often start vibrating together at the same frequency. They “sync up,” sometimes in ways that can seem mysterious, and allow for richer and faster information and energy flows (Figure 1 offers a schematic). Examining this phenomenon leads to potentially deep insights about the nature of consciousness in both the human/mammalian context but also at a deeper ontological level.

Cannabis sativa is an extraordinarily versatile species. Hemp and its cousin marijuana, both C. sativa, have been used for millennia as a source of fibre, oil and for medicinal, spiritual and recreational purposes. Because the consumption of Cannabis can have psychoactive effects, the plant has been widely banned throughout the last century. In the past decade, evidence of its medicinal properties did lead to the relaxation of legislation in many countries around the world. Consequently, the genetics and development of Cannabis as well as Cannabis-derived products are the subject of renewed attention.Here, we review the biology of C. sativa, including recent insights from taxonomy, morphology and genomics, with an emphasis on the genetics of cannabinoid synthesis. Because the female Cannabis flower is of special interest as the site of cannabinoid synthesis, we explore flower development, flowering time well as the species’ unique sex determination system in detail. Furthermore, we outline the tremendous medicinal, engineering, and environmental opportunities that Cannabis bears. Together, the picture emerges that our understanding of Cannabis biology currently progresses at an unusual speed. A future challenge will be to preserve the multi-purpose nature of Cannabis, and to harness its medicinal properties and sustainability advantages simultaneously.

Quantum chemistry must evolve if it wants to fully leverage the benefits of the internet age, where the world wide web offers a vast tapestry of tools that enable users to communicate and interact with complex data at the speed and convenience of a button press. The Open Chemistry project has developed an open source framework that offers an end-to-end solution for producing, sharing, and visualizing quantum chemical data interactively on the web using an array of modern tools and approaches. These tools build on some of the best open source community projects such as Jupyter for interactive online notebooks, coupled with 3D accelerated visualization, state-of-the-art computational chemistry codes including NWChem and Psi4 and emerging machine learning and data mining tools such as ChemML and ANI. They offer flexible formats to import and export data, along with approaches to compare computational and experimental data.

This paper responds to one by Graham Martin and colleagues, who offered a critique of my previous publications on masks for the lay public in the Covid-19 pandemic. I address their charges that my co-authors and I had misapplied the precautionary principle; drawn conclusions that were not supported by empirical research; and failed to take account of potential harms. But before that, I remind Martin et al that the evidence on mask wearing goes beyond the contested trials and observational studies they place centre stage. I set out some key findings from basic science, epidemiology, mathematical modelling, case studies and natural experiments, and use this rich and diverse body of evidence as the backdrop for my rebuttal of their narrowly-framed objections. I challenge my critics’ apparent assumption that a particular kind of systematic review should be valorised over narrative and real-world evidence, since stories are crucial to both our scientific understanding and our moral imagination. I conclude by thanking my academic adversaries for the intellectual sparring match, but exhort them to remember our professional accountability to a society in crisis. It is time to lay straw men to rest and engage, scientifically and morally, with the dreadful tragedy that is unfolding across the world.

This Supporting information includes interactive plots, videos, and data captured while performing evaluation and validation experiments for our paper. 

The construct of wellbeing has been criticised as a neoliberal construction of western individualism that ignores wider systemic issues including increasing burden of chronic disease, widening inequality, concerns over environmental degradation and anthropogenic climate change. While these criticisms overlook recent developments, there remains a need for biopsychosocial models that extend theoretical grounding beyond individual wellbeing, incorporating overlapping contextual issues relating to community and environment. Our first GENIAL model \cite{Kemp_2017} provided a more expansive view of pathways to longevity in the context of individual health and wellbeing, emphasising bidirectional links to positive social ties and the impact of sociocultural factors. In this paper, we build on these ideas and propose GENIAL 2.0, focusing on intersecting individual-community-environmental contributions to health and wellbeing, and laying an evidence-based, theoretical framework on which future research and innovative therapeutic innovations could be based. We suggest that our transdisciplinary model of wellbeing - focusing on individual, community and environmental contributions to personal wellbeing - will help to move the research field forward. In reconceptualising wellbeing, GENIAL 2.0 bridges the gap between psychological science and population health health systems, and presents opportunities for enhancing the health and wellbeing of people living with chronic conditions. Implications for future generations including the very survival of our species are discussed.  

Floral plantings are promoted to foster ecological intensification of agriculture through provisioning of ecosystem services. However, a comprehensive assessment of the effectiveness of different floral plantings, their characteristics and consequences for crop yield across global regions is lacking. Here we quantified the impacts of flower strips and hedgerows on pest control and pollination services in adjacent crops using a global dataset of 529 sites. Flower strips, but not hedgerows, enhanced pest control services in adjacent fields by 16% on average. However, effects on crop pollination and yield were more variable. Our synthesis identifies several important drivers of variability in effectiveness of plantings: pollination services declined exponentially with distance from plantings, and perennial and older flower strips with higher flowering plant diversity enhanced pollination more effectively. These findings provide promising pathways to optimize floral plantings to more effectively contribute to ecosystem service delivery and ecological intensification of agriculture in the future.

Researchers' ability to accurately screen fossil and subfossil specimens for preservation of DNA and protein sequences remains limited. Thermal exposure and geologic age are usable proxies for sequence preservation on a broad scale but are of nominal use for specimens of similar depositional environments. Cell and tissue biomolecular histology is thus proposed as a novel proxy for determining sequence preservation potential of ancient specimens with improved accuracy. Biomolecular histology as a proxy is hypothesized to elucidate why fossils/subfossils of some depositional environments preserve sequences while others do not and to facilitate selection of ancient specimens for use in molecular studies.

IntroductionConsistent with World Health Organization (WHO) advice [1], UK Infection Protection Control guidance recommends that healthcare workers (HCWs) caring for patients with coronavirus disease 2019 (COVID-19) should use fluid resistant surgical masks type IIR (FRSMs) as respiratory protective equipment (RPE), unless aerosol generating procedures (AGPs) are being undertaken or are likely, when a filtering face piece 3 (FFP3) respirator should be used [2]. In a recent update, an FFP3 respirator is recommended if “an unacceptable risk of transmission remains following rigorous application of the hierarchy of control” [3]. Conversely, guidance from the Centers for Disease Control and Prevention (CDC) recommends that HCWs caring for patients with COVID-19 should use an N95 or higher level respirator [4]. WHO guidance suggests that a respirator, such as FFP3, may be used for HCWs in the absence of AGPs if availability or cost is not an issue [1].A recent systematic review undertaken for PHE concluded that: “patients with SARS-CoV-2 infection who are breathing, talking or coughing generate both respiratory droplets and aerosols, but FRSM (and where required, eye protection) are considered to provide adequate staff protection” [5]. Nevertheless, FFP3 respirators are more effective in preventing aerosol transmission than FRSMs, and observational data suggests that they may improve protection for HCWs [6]. It has therefore been suggested that respirators should be considered as a means of affording the best available protection [7], and some organisations have decided to provide FFP3 (or equivalent) respirators to HCWs caring for COVID-19 patients, despite a lack of mandate from local or national guidelines [8].Data from the HCW testing programme at Cambridge University Hospitals NHS Foundation Trust (CUHNFT) during the first wave of the UK severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic indicated a higher incidence of infection amongst HCWs caring for patients with COVID-19, compared with those who did not [9]. Subsequent studies have confirmed this observation [10, 11]. This disparity persisted at CUHNFT in December 2020, despite control measures consistent with PHE guidance and audits indicating good compliance. The CUHNFT infection control committee therefore implemented a change of RPE for staff on “red” (COVID-19) wards from FRSMs to FFP3 respirators. In this study, we analyse the incidence of SARS-CoV-2 infection in HCWs before and after this transition.

The accuracy of rainfall runoff modeling plays a crucial role in the simulation and evaluation of hydrological processes. Numerous physical parameters need to be determined when modeling using SWMM. Automatic calibration helps to achieve improved model accuracy. However, the SWMM model does not have automatic way of calibration. For this purpose, this study is dedicated to combining the NSGA II optimization algorithm with pyswmm to achieve automatic parameter calibration for the swmm model. The swmm model was calibrated and validated using rainfall and runoff measurements from a monitoring catchment located in Taipei City, Taiwan. The results of the study show that the calibrated parameters help to improve the accuracy of the SWMM model quickly compared to relying on manual determination. The relative error of the peak flow rate is lower than 10%. However, the baseflow has a significant impact on the validation of the results. Based on the current research results, it is expected that the proposed method will be exerted on other similar environmental modeling problems.

Scientific outreach activities play an important role in disseminating knowledge, connecting the general public to research and breaking down scientific scepticism barriers. However, the vision impaired community is often disadvantaged when the most common audio-visual approach of scientific communication is applied. Here we integrated tactile clues in the scientific communication of immune processes involved in the autoimmune skin disease psoriasis. We encouraged participation of the vision impaired community by engagement with tactile scientific origami art, a haptic poster and wood carved molecular models. Readily accessible science communication that engages a number of senses is a critical step towards making science more inclusive, and engaging for individuals with a wide range of sensory abilities. The Sensory Science approach aligns with the principles of equity, diversity, and inclusion and helps create a more informed and scientifically literate public.

The ATP-dependent DNA ligase Lig E is present as an accessory DNA ligase in numerous proteobacterial pathogen genomes, including many disease-causing species. Here we have constructed a genomic Lig E knock-out in the obligate human pathogen Neisseria gonorrhoeae and characterised its growth and infection characteristics. This demonstrates that N. gonorrhoeae Lig E is a non-essential gene and its deletion does not cause defects in replication or survival of DNA-damaging stressors. Knock-out strains were partially defective in biofilm formation on an artificial surface as well as adhesion to epithelial cells which coupled with the predicted extracellular/ periplasmic location of Lig E indicates a role in extracellular DNA joining. In addition to in vivo characterisation, we have recombinantly expressed and assayed N. gonorrhoeae Lig E and determined the crystal structure of the enzyme-adenylate engaged with DNA substrate in an open non-catalytic conformation, providing insight into the binding dynamics of these minimal DNA ligases.

Objective Machine learning has been effective in other areas of medicine, this study aims to investigate this with regards to HNC and identify which algorithm works best to classify malignant patients. Design An observational cohort study. Setting Queen Elizabeth University Hospital. Participants Patients who were referred via the USOC pathway between January 2019 and May 2021. Main outcome measures Predicting the diagnosis of patients from three categories, benign, potential malignant and malignant, using demographics and symptoms data. Results The logistic regression-based models with a penalty term worked best on the data, ridge achieving an AUC of 0.7081. The demographic features describing living alone and recreational drug use history were the most important variables alongside the red flag symptom of a neck lump. Conclusion Further studies should aim to collect larger samples of malignant and pre-malignant patients to improve the class imbalance and increase the performance of the machine learning models.

A straightforward electrochemical hydrogenation of benzo[b]thiophene 1,1-dioxides with HFIP as the hydrogen donor has been re-ported in an undivided cell under metal-free conditions. Moreover, the tolerance of various functional groups and scaled-up experi-ments showed the practicability and potential applications of this methodology.

Simulation and optimization of chemical flowsheets rely on the solution of a large number of non-linear equations. Finding such solutions can be supported by constructing machine-learning based surrogates, relating features and outputs by simple, explicit functions. In order to generate training data for those surrogates computationally efficiently, schemes to adaptively sample the feature space are mandatory. In this article, we present a novel family of utility functions to favor an adaptive, Bayesian exploration of the feature space in order to identify regions that are convergent, fulfill customized inequality constraints and are Pareto-optimal with respect to conflicting objectives. The benefit is illustrated by small toy-examples as well as by industrially relevant chemical flowsheets.

Introduction Humanitarian crisis means any event or series of events that are harmful to the health or security of the general population. The Niger Republic is recently facing serious crisis amid the military coup of 26 th of July, 2023. Our fear is that if nothing is done about it quickly, there could be a civil war in Niger and other neighbouring countries. Aim The aim of this present article is to provide comprehensive knowledge about the ongoing humanitarian crisis in Niger, highlighting the factors that caused it and providing possible solutions for them. Methodology A literature search was done about the recent humanitarian crisis amid the military coup in the Niger Republic through databases such as PubMed, ResearchGate, Google Scholar, World Health Organization, United Nations, Online Newspapers and Reports between a 10-year-period. Result We found that the humanitarian crisis amid the military coup in Niger Republic has further amplified the vulnerability of millions of Nigeriens to more problems in the Niger Republic. The number of Nigeriens in need of humanitarian assistance has reportedly increased by 65% from 2.3 million in 2019 to 3.8 million in 2021. More than two million children in Niger have been impacted by the crisis in the country and are in need of humanitarian assistance. Furthermore, other causes of humanitarian crisis in the Niger Republic include; sociodemographic factors, climate change and other natural disasters. Conclusion The humanitarian crisis in Niger, caused by different factors such as socioeconomic stagnation, environmental causes, food insecurity, terrorist activities, and internal displacement is an alarming situation that requires an urgent solution and a response from the international community. There is a need to analyse all the underlying causes of humanitarian crises and find long-lasting solutions for them.

We report on the spectroscopic investigation of common bacteria encountered in biopharmaceutical industries with spectroscopic definition and specificity using mid-infrared laser spectroscopy. This study describes the detection of three different bacteria species using quantum cascade laser spectroscopy coupled to a grazing angle probe (QCL-GAP). Stainless steel substrates were used as support for the bacterial samples. QCL-GAP spectroscopy was assisted by multivariate analysis (MVA) to assemble a powerful spectroscopic technique with classification, identification, and quantification resources. The bacterial species analyzed, Staphylococcus aureus, Staphylococcus epidermidis, and Micrococcus luteus, were used to challenge the technique’s capability to discriminate microorganisms from the same family. Principal component analysis and partial least squares-discriminant analysis differentiated between the bacterial species using QCL-GAP. Spectral differences in the bacterial membrane were used to determine if these microorganisms were present in the samples analyzed. Results herein provided effective discrimination for the bacteria under study with high sensitivity and specificity values.

The present study combined behavioral measures and EEG to investigate the impact of emotional valence on both auditory and written word processing. Participants were first presented with a series of auditory words with varying emotional valence (positive, neutral and negative) produced in neutral tone, which they rated according to valence level. Subsequently they performed a surprise recognition task with written stimuli (half being foils). Our results revealed a significant valence/arousal effect on word recognition; written words with high-arousal and either positive or negative valence were recognized with higher accuracy compared to low-arousal neutral ones. EEG analyses revealed an effect of valence only for words presented in written format; no effects were found for auditory words. For written words, both positive and negative valence elicited a larger P2 response in comparison to neutral valence, indicating allocation of attentional resources. Critically, a reduced N400 was observed only for negative words, suggesting facilitated processing of unpleasant information perhaps due to better encoding during the auditory presentation. Overall, our study provides valuable insights into the cognitive mechanisms involved in integrating emotional information presented in distinct modalities, shedding light on the influence of valence on word recognition.

Background: Primary bone marrow diffuse large B-cell lymphoma (PBM-DLBCL) is a rare hematological malignancy with a poor prognosis. The lack of a clear definition and unified diagnostic criteria for this disease in the WHO classification poses challenges for its diagnosis and management. Patients and Methods: To gain insights into the clinicopathological characteristics of PBM-DLBCL and explore prognostic factors, we conducted a study using data from our center and published literature spanning from 2001 to 2022. A total of 70 patients were included in our analysis. Results: Univariate analysis revealed that patients presenting with B symptoms and higher IPI scores tended to have a poorer prognosis, although statistical significance was not achieved (P>0.05). However, patients who attained a complete response (CR) after initial therapy exhibited better outcomes (P=0.007). Intensive treatment regimens demonstrated potential benefits over general treatment approaches. Additionally, our investigation suggested that rituximab-based chemotherapy was associated with improved prognoses compared to other general regimens. Conclusion: PBM-DLBCL is an aggressive disease with distinct clinical, pathological, and imaging features. It is crucial to understand the clinical characteristics of PBM-DLBCL, identify clinical risks in a timely manner, and determine appropriate treatment regimens.

Background: Recently，epidermal growth factor receptor (EGFR) -targeting drugs have benefited thousands of patients with EGFR mutation-positive (EGFR MUT+) non-small-cell lung cancer (NSCLC). Nevertheless, nearly all patients with NSCLC who were sensitive to first- or second-generation EGFR-tyrosine kinase inhibitors (EGFR-TKIs), finally developed resistance. Therefore, numerous clinicians have focused on improving the clinical effect of first-generation EGFR-TKIs (1st-gen EGFR-TKIs). Methods: To analyze the therapeutic outcomes of individuals with progressive NSCLC, a retroactive assessment was performed on 86 patients who were medicated with only icotinib or combined with pemetrexed and platinum-based chemotherapy at The First Affiliated Hospital of Henan University of Science and Technology (HAUST). Results: Eighty-six patients with NSCLC-bearing EGFR-sensitive mutations were retroactively analyzed. The results showed statistical significance in PFS (P = 0.049) and disease control rate DCR (P = 0.031) between icotinib + chemotherapy and icotinib alone, especially in the brain metastases (P = 0.021) and L-858R mutation subgroups (P = 0.05). According to the findings of the multivariate analysis, treatment (P = 0.033) and EGFR mutation status (P = 0.019) were significant predictive variables. The OS comparison between icotinib + chemotherapy and icotinib alone were not significantly different. The study included a total of 1242 patients, of which 648 obtained combined treatment and 594 obtained first-generation EGFR-TKI monotherapy. Analyzing the relevant data from multiple studies, the results showed significant improvements in ORR (RR: 0.63, 95% CI: 0.49–0.82, P = 0.0006), PFS (RR: 0.61, 95% CI: 0.47–0.79, P = 0.0002), and OS (RR: 0.67, 95% CI: 0.51–0.88, P = 0.004) for those on combination therapy. However, there was also an increase in treatment-emergent AEs among these patients. Conclusion: In summary, administering first-generation EGFR-TKI concurrently with chemotherapy provides an edge in the therapeutic management of locally or severely advanced NSCLC that is EGFR-positive. Therefore, EGFR mutation-positive NSCLC (EGFR MUT+ NSCLC) patients in this condition may find it advantageous to consider using 1st-gen EGFR-TKIs in conjunction with chemotherapy (1st-gen EGFR-TKIs + Chemo).

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