IntroductionThe incidence of papillary thyroid carcinoma (PTC) has rapidly increased worldwide over the past 15 years. Although most PTCs are non-aggressive, but some patients may have poor outcomes due to extracapsular (EC) extension, lymph node (LN) involvement, and distant metastases (1).The trachea is in close proximity to the thyroid gland and can be affected by thyroid cancer spreading beyond the gland. Tracheal invasion by invasive thyroid cancer is rare. Symptoms of tracheal invasion range from none to fatal, including airway obstruction and bleeding. Hoarseness, hemoptysis, and respiratory distress have been reported in some patients with obvious tracheal invasion. Surgery remains the best management for most patients with PTC. Most surgeons follow a special approach, depending on preoperative diagnostics and intraoperative assessment, by means of shaving, partial resection or transverse circumferential (sleeve) resection of the trachea(2). Here, we report a case of PTC with tracheal invasion in a 69-year-old man with successful seven centimeters of trachea resection followed by anastomosis in intact area of trachea.

not-yet-known not-yet-known not-yet-known unknown Background: The innate immune system is activated at the onset of food protein-induced enterocolitis syndrome (FPIES) symptoms. However, the precise mechanism through which this immune response is initiated remains unclear. Objective: We aimed to investigate the proteomic profile of FPIES during symptom development through in-depth serum and saliva proteomic analyses. Methods: We enrolled 17 patients with a previous diagnosis of egg yolk FPIES who underwent an oral food challenge test (OFC) with 5 g of heated egg yolk. Six patients showed positive OFC results, whereas 11 showed negative OFC results. Serum and saliva samples were collected before OFC and 1 and 2 h after ingestion. Serum was also collected at symptom onset. We analyzed serum and saliva peptides using data-independent acquisition-mass spectrometry and compared levels to identify protein groups and pathways important in FPIES symptom development. Results: We detected 4,138 and 7,202 proteins in the serum and saliva, respectively. The OFC-positive group exhibited 609 serum proteins with more than a two-fold change in expression 2 h after OFC, including proteasome subunits and neddylation-related proteins. We identified 304 proteins associated with symptom onset, including those related to the degradation response and neutrophil extracellular trap formation. Proteins related to neutrophil activation increased both in the serum and saliva, regardless of the onset of symptoms. Conclusion: Our findings suggest that changes in protein levels, including proteasome and neddylation-related proteins, may be involved in FPIES pathogenesis and warrant further investigation to address the growing clinical burden imposed by gastrointestinal allergies.

Immunoglobulin E (IgE)-mediated food allergies are reported to affect around 3.5% of children and 2.4% of adults, with symptoms varying in range and severity. While being the gold standard for diagnosis, oral food challenges are burdensome, and diagnostic tools based on specific IgE can be flawed. Furthering our understanding of the mechanisms behind food allergy onset, severity, and persistence could help reveal immune profiles associated with the disease, to ultimately aid in diagnosis. Alterations to cytokine levels and immune cell ratios have been identified, though further research is needed to fully capture the heterogenous nature of food allergy. Moreover, the existence of such immune alterations also raises the question of potential wider systemic effects. For example, recent research has emphasised the existence and impact of neuro-immune interactions and implicated behavioural and neurological changes associated with food allergy. This review will provide an overview of such food allergy-driven neuro-immune interactions, with the aim of emphasising the importance of furthering our understanding of the immune mechanisms underlying IgE-mediated food allergy.

not-yet-known not-yet-known not-yet-known unknown The hepatitis E virus (HEV) is an important causative agent of acute hepatitis (AH). Despite reports of human infection in Brazil, the investigation is not routinely conducted, even in cases of elevated liver enzymes. In this study, two groups were evaluated: group 1 - patients with acute hepatitis A (n=48); group 2 - patients with non-A-C AH (n=47). They were tested by enzyme immunoassay for anti-HEV IgM/IgG and by real-time PCR for HEV RNA detection. The positive sample for HEV RNA was submitted for sequencing. The seroprevalence of anti-HEV IgM and IgG in group 1 was 4% (2/48) and 14.5% (7/48), respectively. Viral RNA was not detected in any sample. In group 2, the anti-HEV IgM positivity was 4.3% (2/47) and IgG 14.9% (7/47). RNA was detectable in one case, which presented a viral load of 222.4 IU/μL and positive anti-HEV IgM/IgG. In the phylogenetic analysis, the genotype identified was HEV-3f. These results indicate that HEV infection should be considered a possible diagnosis in cases of non-A-C AH. The patient identified with acute hepatitis E had recently traveled to Northeast region of Brazil (Garanhuns city in Pernambuco state), where there are reports of high HEV seroprevalence among pigs. The close phylogenetic relationship observed between the sequence characterized in this study and strains isolated from pigs in nearby cities where the patient went suggested a possible zoonotic transmission in this region. This study highlights the importance of expanding studies and improving surveillance to understand and manage HEV infections nationwide better.

HIV and hepatitis B virus (HBV) coinfection has been associated with higher risk of morbidity and mortality. HBV-active antiretroviral regimens has significantly improved the outcome of coinfected people. Although bictegravir/emtricitabine/tenofovir alafenamide (B/F/TAF) is safe and efficacious in the treatment of HIV, there are few randomized studies on treatment of HIV/HBV coinfection. This open label switch study enrolled adults with HIV/HBV coinfection from two clinical centers. Participants were switched from their current antiretroviral regimen (regardless of viral suppression) to B/F/TAF, taken once daily for 48 weeks. Primary endpoints were proportion of participants with HIV RNA <50 copies/mL and HBV DNA <29 IU/mL at Week 24. Twenty-eight participants were enrolled with a median age of 51 years - majority were Black (89%) and male (86%). At baseline, 71% (20/28) and 79% (22/28) were HIV and HBV suppressed, respectively, and 64% (18/28) were suppressed for both. At week 24, 89% (25/28) and 86% (24/28) were HIV and HBV suppressed, respectively, and 82% (23/28) were suppressed for both. Most common treatment-related adverse event was nausea (2/28). None discontinued due to an adverse event. No serious adverse events or hepatitis flares observed. B/F/TAF is a safe and suitable option for treatment of HIV/HBV coinfected patients.

A document by Sever Yildiz G. Click on the document to view its contents.

BACKGROUND:There is a specific pathway named vestibulo-cochlear pathway runs through the inferior vestibular nerve to cochlea. vestibular neurectomy (V.N) is a well established procedure that is performed to control intractable Meniere disease. However, the function and the histopathological changes of the cochlea that could be occurred after vestibular neurectomy were not fully studied. OBJECTIVE:Experimentally test the effect of vestibular nerve neurectomy on the function and histopathology of the cochlea. EXPERIMENTAL PROCEDURES: The study was conducted on 20 normal male adult pigmented guinea pigs (Cavia porcellus). First, each animal was tested with Distortion Product Otoacoustic Emissions (DPOAEs) preoperatively then vestibular neurectomy (V.N) was performed on the right side through suboccipital modified retrosigmoid approach. We tested the DPOAEs postoperatively; After 8 weeks, Guinea pigs were euthanized the cochlea of guinea pig was processed for light microscope and transmission electron microscope examination to observe the outer hair cell count, and spiral ganglion cell density in the operated ear compared to contralateral non operated cochlea of the same guinea pig. RESULTS:There was a significant decrease in spiral ganglion cell density in the operated side compared to the non-operated side. However, there was no significant difference in outer hair cell count or DPOAEs between the two sides, except for a significant increase in DPOAEs at 2 KHz in the operated side. CONCLUSIONS:The results suggest that vestibular neurectomy may affect spiral ganglion cell density but not necessarily outer hair cell count or DPOAEs, and the relationship between these variables is complex and could be frequency-depende

not-yet-known not-yet-known not-yet-known unknown Introduction High-power short-duration(HPSD) radiofrequency catheter ablation(RFCA) for atrial fibrillation(AF) has been gradually applied in clinical practice.However,the efficacy and safety of HPSD compared to traditional low-power long-duration (LPLD) ablation are not definitive conclusion. In addition, Zero-fluoroscopy catheter ablation technique has also emerged as a novel method in present ,However research on the combination of zero-fluoroscopy procedure with HPSD catheter ablation for AF are unknown. Objective To evaluate the efficacy and safety of HPSD and LPLD using intracardiac echocardiography (ICE) combined with electroanatomic mapping (EAM) reconstruction for zero-fluoroscopy during RFCA for AF. Methods A total of 173 patients undergoing RFCA for AF were divided into a HPSD(45-50w) group (n=87) and a LPLD (30-35w)group (n=86). The procedure was performed using ICE combined with EAM to achieve zero-fluoroscopy. Both groups underwent routine pulmonary vein isolation(PVI) .There are additional linear ablations for persistent AF at the left atrial roof line, left atrial posterior wall line, mitral isthmus line, and tricuspid isthmus line if necessary. The duration of the procedures, efficacy, short-term and one year successful rates, as well as procedure complications were compared between the two groups. Results The procedure time and ablation time in the HPSD group were significantly shorter than those in the LPLD group(115.8±30.8 vs 130.5±26.3, P =0.001; 14.9±2.3 vs 30.0±4.1, P =.000). There was no difference between the two groups in terms of TSP time(50.0±10.9 vs 51.7±9.0, P =0.273), immediate success rate of PVI(100% vs 100%, P =1.000), single-loop isolation rate of PVI(98.9% vs 95.3%, P =.169), and number of ablation points(71.6±8.4 vs 74.2±14.6, P =.159). At 12 months follow-up, sinus rhythm was maintained in 77 cases in the HPSD group and 74 cases in the LPLD group with no significant difference between them (88.5% vs 86.0%, P =.583). There were 5 and 3 complications in the HPSD group and the LPLD group, respectively, with no difference between the two groups(3.4% vs 5.8%, P =.459). There were no stroke,esophageal atrial fistulae or deaths in either group. Conclusion ICE combined with EAM guidance for zero-fluoroscopy HPSD catheter ablation for atrial fibrillation is safe, reliable and repeatable, and the 1-year success rate is similar to that of traditional power, with a trend of improvement.

Fluorescent molecular probes are commonly used to detect active substances. However, in variable living microenvironmental systems, most of conventional aromatic fluorescent probes often suffer from aggregation-caused quenching (ACQ) due to π-π stacking, which severely limit their selectivity and sensitivity. To tackle this challenge, a predictable supramolecular strategy, which offers significant spatial effects to prevent fluorophore’s intermolecular π-π stacking at the molecular level, was proposed to design fluorescent probes. Herein, supramolecular probe RAA@Q[8] was successfully integrated by loading an adamantane-modified Rhodamine derivative (RAA) into cucurbit[8]uril (Q[8]) via the host-guest recognition principle. Intriguingly, the original highly clustered RAA-agminated spheroids become discrete supramolecular organic framework octahedrons (RAA@Q[8]), suggesting that the molecular aggregation behavior is well-modulated. This encouraging result is important for precise detection of plant signaling molecules such as salicylic acid (SA) in various environments. Experimental investigations found that RAA@Q[8] was 2.2-fold more sensitive than RAA for detecting SA, with high selectivity and anti-interference, and a low detection limit of 3.0×10 -8 M. Importantly, in complicated living microenvironments, RAA@Q[8] achieved a precise recognition and imaging of SA on pea sprouts and HEK-293 cells. This study offers a guidance for future development of host-guest supramolecular fluorescent probes that are opposite to the intractable ACQ obstacle.

The emergence of multidrug-resistant bacteria has increased the need for potent antibacterial agents. Essential oils (EO) are promising alternatives; however, their volatile, unstable, and hydrophobic nature challenges their bioavailability. In this study, we describe enhanced synergistic antioxidant and antibacterial effect of stable oil-in-water (O/W) nanoemulsions (NE) formulated from blends of thyme, cinnamon bark, black pepper, and garlic essential oils, using a high-energy ultrasonication incorporating a surfactant (tween 80, HLB=15) and co-surfactant (glycerol). Average droplet size of ~44-88 nm and polydispersity index of 0.2-0.3 were determined using dynamic light scattering. The spherical shape and size of the nanoemulsions were confirmed by transmission electron microscopy. The nanoemulsions were thermodynamically stable up to three months after the heating-cooling cycle (40↔ 4°C) and freeze-thaw cycle (-21°C) respectively. GC-MS and FT-IR analysis identified structures and functional groups of diverse volatile components. DPPH antioxidant assay demonstrated >16-fold enhanced free radical scavenging capacity of NE compared to blended EO and pure oils; ABTS assay exhibited similar trend. Antibacterial effects was enhanced, with MIC values halved when the blended EO was nano-encapsulated, against a resistant extended-spectrum lactamase (ESBL) strain of K. pneumoniae from 1.25 to 0.625 mg/ml , and 0.625 to 0.312 mg/ml for E. coli, S. aureus and S. typhimurium, while it remains unchanged for P. aeruginosa (1.25 mg/ml). Scanning electron microscopy highlighted significant alteration in treated bacteria’s membrane integrity. Therefore, we have successfully formulated stable nanoemulsions exhibiting enhanced synergistic antioxidant and antibacterial activities with potential applications in the food and feed industry.

Eating disorders (ED) and personality disorders (PD) co-occur together frequently, and the latter need to be considered by the treating clinicians as they can hinder treatment effectiveness or, if left unaddressed, can lead to relapse. These persons present with a combination of ED symptoms and behaviours, interpersonal problems and global suffering and often have difficulties forming and sustaining a therapeutic alliance. How can we address this condition so as to make ED treatment more effective? We describe the story of Silvia, a 34 years old woman with Binge Eating Disorder (BED) and PD treated with Metacognitive Interpersonal Therapy. She entered treatment with frequent binges and was seriously overweight (Body Mass Index= 36.7). She had difficulties describing her inner states and understanding why she binged, so she could not control them. During therapy, starting from the information coming from the food diary, she gradually becomes aware of how she processes underlying symptoms and interpersonal behaviour. The therapist used a combination of CBT techniques and experiential work, such as guided imagery, to foster change in both the ED and PD domains. By treatment termination, Sivia no longer suffered from either BED or PD and lost 10kg. This case is an example of how it is possible to combine aspects of treatment targeting ED with attention to PD features in an effective way. It also invites researchers to consider ED/PD comorbidity so as to reduce dropouts and increase treatment effectiveness

Plant-microbe associations are ubiquitous, but parsing the contributions of dispersal, host filtering, competition, and the environment on microbial community composition is challenging. Floral nectar-inhabiting microbes offer a tractable system to disentangle community assembly processes. We inoculated a synthetic community of yeasts and bacteria into nectars of 31 phylogenetically diverse plant species while excluding pollinators. We monitored weather conditions and, after 24 hours, collected and cultured communities. We found a strong signature of plant species on resulting microbial abundance and community composition, in part explained by plant phylogeny and nectar peroxide content, but not measured floral morphological traits. Higher maximum and minimum temperatures increased microbial growth overall and favored certain microbes over others. Our work supports the roles of plant identity and abiotic conditions in assembly and growth of plant-associated microbial communities and finds evidence for diversity-productivity relationships within plant-associated microbiomes.

The comprehension of the reciprocal interaction between root development and its co-adapted beneficial microbes in response to elevated CO 2 (eCO 2) will facilitate the identification of nutrient-efficient cultivars for a sustainable agriculture. Here systemically morphological, anatomical, chemical and gene expression assays performed under eCO 2 highlight the divergent root differentiation driven endodermal barrier development with respect to the L-/S-shaped lateral roots under low nitrogen conditions in rice. Next, by metabolome and endodermal-cell specific RNA sequencing we showed that rice adapted to eCO 2 by spatially recruiting diazotrophs through flavonoid secretion in L-shaped lateral roots. To the end, using a rice Casparian strip mutant Oscasp1-1 we validated such root differentiation driven specific recruitment of a diazotrophic family Oxalobacteraceae implicated in plant tolerance to low nitrogen availability. Our work indicates that rice could coordinate nutrient uptake and root differentiation by the recruitment of diazotrophs in L-shaped lateral roots under climate change.

An organic branding is one of the most unique processes to build a brand. Most of the companies are trying to build their brand using paid branding through some well-known platforms like Google, Facebook, etc. Sometimes this method may work, but it may not have a far-reaching effect. Creating some hype is easy with paid branding. Creating mass-trust is not possible with paid branding. Moreover, it is expensive. Every company want a lot of organic traffic. The high volume of traffic will increase the orders for a company. For example, search for any online services such as software service providing website or e-commerce online stores or job boards or any other goods, the main revenue growth depends on the amount of traffic routed to their website.

In the dynamic landscape of entrepreneurship, where opportunities abound and innovation thrives, Entrepreneurship: Navigating the Future with Data Science and AI” presents a groundbreaking approach to cultivating and empowering the next generation of business leaders. Authored with a comprehensive understanding of the intersection between technology and entrepreneurial endeavors, this paper offers a segmented approach that delves into the realms of data science, artificial intelligence, audience nurturing, and emerging trends. In employed and self-employed worlds, emphasizing a paradigm shift towards discussing opportunities rather than individuals. The core premise revolves around leveraging artificial intelligence, data-driven marketing, and audience nurturing as pivotal tools for fostering entrepreneurship. The paper introduces a novel segmented model, markets, societies, and political landscapes by strategically promoting entrepreneurship. Drawing on the computational power of data science, statistical methods, and computer science algorithms, the book advocates for the analysis of diverse and unstructured datasets to encourage risk-taking and entrepreneurial activities, particularly among students. The segmented model identifies and supports small risk-takers, utilizing specific data points sourced with consent from interested students, government schemes, private initiatives, and entrepreneurial supporting businesses. As the narrative unfolds, readers are guided through the intricacies of implementing this segmented approach, involving industry experts, instructors, and mentors. The paper proposes few concepts on ’entrepreneurship,’ any one can build a user-friendly ecosystem designed to connect entrepreneurs, investors, and trainers seamlessly. Key features include user segmentation, a resource hub, networking platforms, business counseling integration, and events and webinars calendar, among others. The significance of artificial intelligence technologies is thoroughly explored, with a focus on resource acquisition, opportunity recognition, product development, organization creation, growth, and commercialization. Practical applications of AI in online communication, prototyping, and mentorship further underscore the transformative role of technology in the entrepreneurial journey. The latter part of the paper introduces a proposed algorithm for connecting startups with potential investors, emphasizing the importance of factors like industry alignment, business stage, investment preferences, and expertise. The algorithm is presented in Python, providing a tangible and implementable solution for fostering successful collaborations. A noteworthy addition to the narrative is the integration of machine learning in the matchmaking process. In this paper we will discuss the machine learning model to predict compatibility scores, showcasing a more dynamic and data-driven approach to pairing startups with investors. The step-by-step guide includes the generation of synthetic data, training the ML model, and using predictions to match startups with investors. The Entrepreneurship serves as a comprehensive guide for aspiring entrepreneurs, seasoned business leaders, and anyone intrigued by the transformative power of data science and artificial intelligence in shaping the future of entrepreneurship. It invites readers to embrace innovation, leverage technology, and navigate the complexities of the business landscape with strategic insight, ultimately contributing to the growth and success of ventures in the evolving entrepreneurial ecosystem.

Alfalfa ( Medicago sativa L.) is a crucial and widely grown forage legume that faces yield challenges due to salinity stress. In this study, an R2R3-MYB transcription factor (TF), MsEOBI was characterized from alfalfa. Its function and gene regulatory pathways were studied in alfalfa seedlings. The nuclear-localized MsEOBI acts as a transcriptional activator. MsEOBI enhances salinity tolerance of alfalfa by promoting flavonoids and lignin biosynthesis, as well as scavenging reactive oxygen species (ROS). MsEOBI also promote pollinator attraction and seed yield by activating volatile phenylpropanoid biosynthesis. Yeast one-hybrid, dual-luciferase, and ChIP-qPCR assays showed that MsEOBI binds directly to the promoter of MsPAL1, a key enzyme in the phenylpropanoid pathway to activate its expression. Overexpression of MsPAL1 in alfalfa enhances salinity tolerance. These findings shed light on the functions of the MsEOBI-MsPAL1 module in alfalfa and offer valuable genetic resources for the breeding of salt stress-resistant varieties in the future.

not-yet-known not-yet-known not-yet-known unknown A novel Pseudomonas aeruginosa phage, designated as PaYy-2, has been isolated from a lake in China and its genome meticulously sequenced and characterized. The PaYy-2 phage possesses a 92,348 base pair double-stranded DNA genome that encodes for 168 proteins, exhibiting a 68% similarity to the genome of the known Pseudomonas phage YS35. Phylogenetic analysis reveals that the putative RNA polymerase of PaYy-2 shares a 94% similarity with that of Pseudomonas phage SRT6, and its putative terminase large subunit exhibits a 96% resemblance to phage YS35, both of which are classified under the Pakpunavirus genus. Morphological examination via transmission electron microscopy (TEM) has provided insights into the phage’s tail and particle morphology. These collective findings underscore the classification of PaYy-2 as a distinct species within the Pakpunavirus genus of the family Myoviridae.

This article discusses the use of classification of web visitors and determination of branding quality using AI in effort to redesign digital marketing. AI in its various forms such as machine learning, natural language processing, and computer vision helps businesses to better understand their users' behavior, better understand the context of supplied content and improve user experience. The application of AI in the management of the websites offers features such as Real-time monitoring, automated content tuning, and Analytics for predictions. Automated tools can analyze who is visiting the site, what kind of work they are doing in terms of SEO, and how to assist with creating high-quality content. Also, AI helps with mass and targeted promotions like recommended products and services, variable rates of prices, etc. AI can help unlock significant benefits for businesses, across the board and lead to enhanced engagement in the digital space and thus gives a competitive advantage in the market. The article also discusses investment in training and education for consumers to ensure them remain relevant with emerging technologies in AI and the market. By way of illustration and analysis, the article clearly outlines how the incorporation of AI in organizational functions can bring about operational efficiencies and cost savings, as well as result in remarkable improvements in branding and marketing strategies.

The paper titled “Artificial Intelligence-Based Cloud Planning and Migration to Cut the Cost of Cloud” aims at examining how AI can be implemented to improve cloud planning and migration in a bid to reduce their costs. The proposal is concerned with the utilization of multiple AI techniques such as machine learning models, natural language processing and reinforcement learning to manage the migration process in the cloud. In incorporating AI within the transitions, the paper establishes how organizations improve organizational resource allocation, productivity stability, and security during Cloud transitions. It provides detailed pseudocode of the scenario, making the content sufficiently intelligible to the IT professionals who wish to implement these AI algorithms. In this regard, this paper helps to fill the gap that has been demonstrated in the current literature regarding the link between theoretical uses of AI and its application in cloud migration towards enhancing the deployment efficacy and cost-efficiency of cloud services.

This research focuses on the topic of using AI in color variant management in products to enhance the appeal and performance of the products in the marketplace, by incorporating artificial intelligence, deep learning, and neural network systems. Applying consumers and products information, preferences, buying history and sales history, WE created AI models to predict and change product colors in real-time. The complete workflow used comprises data gathering, processing, and feature extraction, model training, integration of the color adjustment software tools, and finally, testing and validation. The efficiency of such AI-driven interventions was analyzed through the consumer satisfaction indices, the sales results, and the engagement data based on the consumption of digital platforms. This study demonstrates valuable potential of AI to improve product design application and development while providing valuable suggestion for Business adapting and improving market outcomes according to the changing consumer trends. Such an application of AI implements a new best practice in the ways of enhancing futuristic consumer-oriented marketing approaches.

This paper discusses the potential of machine learning, data science, and natural language processing (NLP) in mitigating the incidence of spoofing and financial risks hinged on cyber threats. Another one is spoofing; it is the act of impersonating legitimate entities to gain unauthorized information and it is indeed a threat to the public and companies to some extent. The research introduces two primary methodologies to combat spoofing: an email filtering system using a machine learning algorithm and an encryption and decryption system using a Caesar Cipher and Python programming language. It distinguishes between approved domains and unapproved domains by using machine learning and successfully filters out phishing emails from reaching the intended clients. This study also illustrates how to conduct email domain verification using MongoDB Atlas, which a database is containing approved vendors’ domains, to reduce spoofing. Specifically, incorporating NLP helps the system analyze raw data to categorize it and identify patterns potentially leading to a spoofing attempt, enhancing the spoofing detection and prevention of the system. The paper also presents arguments that require awareness and integration of new technologies in the security frameworks. Hence, incorporating machine learning, data science, and NLP presents robust, versatile, and cost-effective solutions to enhance cybersecurity and ultimately protect vital information and organizations’ monetary loss due to cybercrimes.

Background: Schizophrenia is a significant mental disorder that adversely affects the quality of life of individuals. In schizophrenia, numerous psychotherapeutic interventions can alleviate symptoms. Aims: The aim of this study is to reveal the effectiveness of psychotherapeutic interventions applied to individuals diagnosed with schizophrenia on the symptoms of the disease. Material and Methods: For this study, data were obtained by searching Web of Science, PubMed, Google Scholar, EBSCOhost, Google Scholar, and YÖK Thesis Center databases between December 2023 and January 2024. Results and Discussion: After all reviews were completed, 6 studies were included in the study. In this meta-analysis, it was found that psychotherapeutic interventions applied to individuals with schizophrenia had a significant effect on the symptoms of the disease and provided significant improvements (SMD: 1.483, 95% CI: 0.346 to 2.620; Z=2.557; p<.05). Conclusion: Nurses can play an effective role in reducing the symptoms of individuals with schizophrenia and contribute to their recovery.

Objective: To analyze the characteristics of potential profiles of psychological distress in adolescents and young adults (AYAs) with thyroid cancer and to explore the population characteristics and factors. Methods: 213 AYAs with thyroid cancer were assessed using the general information questionnaire, Strategies Used by People to Promote Health (SUPPH), and the specific Cancer Distress Scales for Adolescents and Young Adults (CDS-AYA) from February to July 2023. Results: Three potential profiles of psychological distress were finally identified: “lower” (67.1%), “general” (25.8%), and “higher” (7.1%) psychological distress groups. Logistic regression analysis showed that the presence of underlying disease, treatment modality, tumor-node-metastasis (TNM), and self-management efficacy were the factors in the potential psychological distress profiles among AYAs with thyroid cancer. Conclusion: This study identified heterogeneity in psychological distress among AYAs with thyroid cancer and classified it into three profiles. Factors influencing the potential characteristics of psychological distress in thyroid cancer patients include underlying disease, treatment modality, TNM, and self-management efficacy. Nurses should be attentive to the psychological well-being of AYAs with thyroid cancer. Nurses could adopt different interventions according to the individual characteristics of patients, to reduce psychological distress and improve mental health.

The traditional view holds that the global distribution of biological nitrogen fixation (BNF) in terrestrial ecosystems is primarily driven by climate, associating certain warm, wet low-latitude regions with higher BNF rates. However, this view fails to explain the low free-living BNF rates observed in these regions. Here, we conducted two field experiments and a global synthesis to assess the regulatory patterns of free-living BNF at both regional and global scales. The field experiments showed that the regional distributions of litter free-living BNF did not necessarily peak at warm and wet sites, due to co-regulation by climate and substrate stoichiometry (especially C : [N : P]). Subsequently, the global synthesis demonstrated that these phenomena and co-regulatory patterns persisted in free-living BNF in litter and other substrates (e.g., soil) at global scale. Our findings highlight the important role of substrate stoichiometry in regulating the spatial distribution of free-living BNF.