Text Terms Research Articles

A Named Entity Recognition Model for Chinese Electricity Violation Descriptions Based on Word-Character Fusion and Multi-Head Attention Mechanisms

Due to the complexity and technicality of named entity recognition (NER) in the power grid field, existing methods are ineffective at identifying specialized terms in power grid operation record texts. Therefore, this paper proposes a Chinese power violation description entity recognition model based on word-character fusion and multi-head attention mechanisms. The model first utilizes a collected power grid domain corpus to train a Word2Vec model, which produces static word vector representations. These static word vectors are then integrated with the dynamic character vector features of the input text generated by the BERT model, thereby mitigating the impact of segmentation errors on the NER model and enhancing the model’s ability to identify entity boundaries. The combined vectors are subsequently input into a BiGRU model for learning contextual features. The output from the BiGRU layer is then passed to an attention mechanism layer to obtain enhanced semantic features, which highlight key semantics and improve the model’s contextual understanding ability. Finally, the CRF layer decodes the output to generate the globally optimal label sequence with the highest probability. Experimental results on the constructed power grid field operation violation description dataset demonstrate that the proposed NER model outperforms the traditional BERT-BiLSTM-CRF model, with an average improvement of 1.58% in precision, recall, and F1-score. This demonstrates the effectiveness of the model design and further enhances the accuracy of entity recognition in the power grid domain.

How do we measure the costs, benefits, and harms of sharing data from biomedical studies? A protocol for a scoping review.

The benefits of sharing participant-level data, including clinical or epidemiological data, genomic data, high-dimensional imaging data, or human-derived samples, from biomedical studies have been widely touted and may be taken for granted. As investments in data sharing and reuse efforts continue to grow, understanding the cost and positive and negative effects of data sharing for research participants, the general public, individual researchers, research and development, clinical practice, and public health is of growing importance. In this scoping review, we will identify and summarize existing evidence on the positive and negative impacts and costs of data sharing and how they are measured. Eligible studies will report on qualitative or quantitative approaches for measuring the cost of data sharing or its impact on participant privacy, individual or public health, researcher's careers, clinical or public health practice, or research or development. The systematic search strategy uses MeSH and text terms and is tailored for Ovid Medline, Cumulative Index to Nursing and Allied Health Literature, and Web of Science. We will apply the Arskey and O'Malley scoping review methodology. We selected a scoping rather than a systematic review approach to address multiple related questions and provide guidance related to an emerging field. Two reviewers will conduct the title-abstract and full-text screening and data charting independently. Discrepancies will be resolved through consensus and results will be summarized in a narrative form. Research participants, investigators, regulatory groups, ethics review committees, data protection officers, and funders cannot make informed decisions or policies about data reuse without appropriate means of measuring the effects, positive or negative, and cost of data sharing.

Advanced machine learning techniques for fake news detection: A comprehensive analysis

The rise of fake news has become a significant global concern, undermining public trust and information integrity. This study explores the application of advanced machine learning algorithms for detecting fake news, leveraging a balanced dataset of real and fake news articles. Through rigorous preprocessing, including text cleaning and Term Frequency-Inverse Document Frequency (TF-IDF) vectorization, the study enhances data quality and model performance. Five machine learning models—Random Forest, Support Vector Machine (SVM), Neural Networks, Logistic Regression, and Naïve Bayes—are systematically evaluated using metrics such as accuracy, precision, recall, and F1-score. Results indicate that the Random Forest Classifier outperforms other models with an accuracy of 99.95% and balanced performance across metrics, demonstrating its robustness in distinguishing fake from real news. SVM and Neural Networks also achieve high accuracy, showcasing their capability in handling complex data. Logistic Regression and Naïve Bayes, while computationally efficient, exhibit relatively lower performance. The findings underscore the importance of ensemble methods and sophisticated preprocessing techniques in detecting fake news effectively. This research provides a methodological framework for scalable fake news detection, offering valuable insights for developing automated systems to combat misinformation and promote informed decision-making in the digital age.

¿PERSUADEN LOS NIÑOS DE LA MISMA MANERA A SUS AMIGOS QUE A LOS ADULTOS? UN ESTUDIO CON ESCOLARES DE QUITO, ECUADOR

Introduction. The ability to persuade requires understanding how through language one can influence the mental states (EEMM) of the persuaded, so that they adopt a belief, attitude or idea that, in turn, leads them to perform some action (To et al., 2016). It has therefore been linked to theory of mind, having been shown that a greater understanding of mind is associated with a greater variety and frequency of terms referring to EEMM (Longobardi et al., 2015). However, there are no known studies on child persuasion that analyze mental state language. Objective. The aim of this study is to analyze the frequency of use of mental state terms in short persuasive texts of school-aged children, and to test the effect of addressee: asymmetry (equal vs adult), familiarity (own mother vs friend's mother) and authority (friend's mother vs school principal). Method. The participants were 117 schoolchildren (75 girls) aged 7 to 12 years from Quito (Ecuador). Each participant wrote, at an appropriate time and place, four short texts, addressed respectively to: a friend, her own mother, a friend's mother and the school principal, in an attempt to convince them of the same thing. For each text, the frequency of occurrence of EEMM terms was analyzed following the proposal of Pinto et al. (2017): Cognitive, Volitional, Emotional and Moral. Results. Two Repeated Measures ANOVAs indicate significant differences in the total frequencies of EEMM terms (in order: Volitional, Moral, Emotional, Cognitive) and that there are no significant differences in the frequency of total EEMM terms by addressee. However, for each addressee separately, four Repeated Measures ANOVAs revealed different distribution patterns in EEMM terms. Friends as addresses differ from adults by generating much higher frequency of Emotional terms and much lower frequency of Moral terms. Significantly more Moral and Cognitive terms are used with one's own mother than with a friend's mother. With the mother of a friend, significantly more Emotional terms are used than with the school principal. Discussion. The data allow us to demonstrate the effect of asymmetry (differences between text addressed to a friend and adults), familiarity (between text addressed to one's own mother and that of a friend) and authority (between text addressed to a friend's mother and the school principal) in the use of terms referring to Cognitive, Volitional, Emotional and Moral EEMM by children from 7 to 12 years of age.

Reporting of nutritional screening, status, and intake in trials of nutritional and physical rehabilitation following critical illness: a systematic review.

Surviving critical illness leads to prolonged physical and functional recovery with both nutritional and physical rehabilitation interventions for prevention and treatment being investigated. Nutritional status and adequacy may influence outcome, but no consensus on which nutritional-related variables should be measured and reported in clinical trials exists. This study aimed to undertake a systematic review investigating the reporting of nutritional screening, nutritional status, and nutritional intake/delivery in randomized controlled trials (RCTs) evaluating nutritional and/or physical rehabilitation on physical and functional recovery during and following critical illness. Five electronic databases (MEDLINE, Web of Science, EMBASE, CINAHL, and Cochrane) were searched (last update 9 August, 2023). Search terms included both free text and standardized indexed terms. Studies included were RCTs assessing nutritional and/or physical interventions either during or following intensive care unit (ICU) admission in adults (18 y or older) with critical illness, and who required invasive mechanical ventilation for any duration during ICU admission. Study quality was assessed using the Cochrane Collaboration Risk of Bias tool for RCTs and descriptive data synthesis was performed and presented as counts (%). n t RESULTS: In total, 123 RCTs (30 nutritional, 87 physical function, and 6 combined) were included. Further, ≥1 nutritional variable was measured and/or reported in 99 (80%) of the studies including BMI (n = 69), body weight (n = 57), nutritional status (n = 11), nutritional risk (n = 10), energy delivery (n = 41), protein delivery (n = 35), handgrip strength (n = 40), and other nutritional-related muscle variables (n = 41). Only 3 studies were considered to have low risk of bias in all categories. Few RCTs of physical rehabilitation measure and report nutritional or related variables. Future studies should measure and report specific nutritional factors that could impact physical and functional recovery to support interpretation where studies do not show benefit. This protocol was preregistered at PROSPERO as CRD42022315122.

Semantic features of English terms in Russian-language job vacancy texts for lawyers

Semantic features of English terms in Russian-language job vacancy texts for lawyers

Deepfake Detection on Social Media: Leveraging Deep Learning and Fast Text Embeddings for Identifying Machine-Generated Tweets

Recent improvements in natural language generation offer a new means to influence public opinion on social media. Moreover, developments in language modelling have considerably augmented the generative capacities of deep neural models, equipping them with improved competencies for content creation. As a result, text-generative models have gained significant potency, enabling adversaries to leverage these capabilities to enhance social bots, facilitating the creation of authentic deepfake postings and swaying public conversation. In order to address this issue, trustworthy and efficient techniques for detecting social media deepfakes are essential. Automated text on Twitter has been identified in recent studies. To determine if tweets are generated by humans or bots, this study employs the publicly available Tweepfake dataset and a basic deep learning model that makes use of word embeddings. Using a CNN architecture, FastText word embeddings can detect deepfake tweets. This study utilised many machine learning models as baseline approaches to demonstrate the higher performance of the proposed approach. Some of the fundamental techniques used here were Term Frequency, Fast Text subword embeddings, FastText, and Term Frequency-Inverse Document Frequency. Additional comparisons with other DL models, such as CNN-LSTM and LSTM, demonstrate the effectiveness and benefits of the suggested approach in precisely resolving the issue. The experimental results demonstrate that Twitter data may be efficiently and accurately classified with a 93% accuracy rate using CNN architecture and FastText embeddings.

Psychiatric Symptoms in Wilson's Disease-Consequence of ATP7B Gene Mutations or Just Coincidence?-Possible Causal Cascades and Molecular Pathways.

Wilson's disease (WD) is an autosomal recessive disorder of copper metabolism. The genetic defect in WD affects the ATP7B gene, which encodes the ATP7B transmembrane protein, which is essential for maintaining normal copper homeostasis in the body. It is primarily expressed in the liver and acts by incorporating copper into ceruloplasmin (Cp), the major copper transport protein in the blood. In conditions of excess copper, ATP7B transports it to bile for excretion. Mutations in ATP7B lead to impaired ATP7B function, resulting in copper accumulation in hepatocytes leading to their damage. The toxic "free"-unbound to Cp-copper released from hepatocytes then accumulates in various organs, contributing to their damage and clinical manifestations of WD, including hepatic, neurological, hematological, renal, musculoskeletal, ophthalmological, psychiatric, and other effects. While most clinical manifestations of WD correspond to identifiable organic or cellular damage, the pathophysiology underlying its psychiatric manifestations remains less clearly understood. A search for relevant articles was conducted in PubMed/Medline, Science Direct, Scopus, Willy Online Library, and Google Scholar, combining free text and MeSH terms using a wide range of synonyms and related terms, including "Wilson's disease", "hepatolenticular degeneration", "psychiatric manifestations", "molecular mechanisms", "pathomechanism", and others, as well as their combinations. Psychiatric symptoms of WD include cognitive disorders, personality and behavioral disorders, mood disorders, psychosis, and other mental disorders. They are not strictly related to the location of brain damage, therefore, the question arises whether these symptoms are caused by WD or are simply a coincidence or a reaction to the diagnosis of a genetic disease. Hypotheses regarding the etiology of psychiatric symptoms of WD suggest a variety of molecular mechanisms, including copper-induced CNS toxicity, oxidative stress, mitochondrial dysfunction, mitophagy, cuproptosis, ferroptosis, dysregulation of neurotransmission, deficiencies of neurotrophic factors, or immune dysregulation. New studies on the expression of noncoding RNA in WD are beginning to shed light on potential molecular pathways involved in psychiatric symptomatology. However, current evidence is still insufficient to definitively establish the cause of psychiatric symptoms in WD. It is possible that the etiology of psychiatric symptoms varies among individuals, with multiple biological and psychological mechanisms contributing to them simultaneously. Future studies with larger samples and comprehensive analyses are necessary to elucidate the mechanisms underlying the psychiatric manifestations of WD and to optimize diagnostics and therapeutic approaches.

MicroRNAs and hypospadias: A systematic review.

The aim of the present study was to summarize what is known about the role of microRNAs (miRNAs/miRs) in relation to hypospadias. Therefore, a systematic review was performed by consulting the electronic databases, MEDLINE (PubMed) and Embase. The search strategy consisted of both MeSH and free text terms, including hypospadias AND miRNA. Only articles written in the English language were included. In the selection process, three authors assessed the studies defined through the search strategy based on titles and abstracts. The authors then analyzed the complete articles and selected studies conforming to the eligibility criteria. Studies that did not align with the adopted criteria were excluded based on the limits set by the initial search strategy: Publication details, study design and participant characteristics. Articles presenting original data on miRNAs associated with hypospadias and including information on miRNA detection and analysis methods were extracted from the selected articles. The included studies presented miRNA extraction from blood samples, preputial or penile tissues, urethral epithelium and/or foreskin fibroblasts. The compiled data focused on the regulatory role of miR-494, miR-145, miR-6756-5p, miR-182, miR-200c, miR-210 and miR-1199-5p in vital cell biological processes, such as wound healing, and cell proliferation, growth and apoptosis. These results proposed that miRNAs may serve as key molecules that merit further investigation; for instance, they may be used as potential biomarkers, diagnostic markers and, eventually, as pharmaceutical agents in hypospadias.

Evaluating a generative artificial intelligence accuracy in providing medication instructions from smartphone images

BackgroundThe Food and Drug Administration mandates patient labeling materials like the Medication Guide (MG) and Instructions for Use (IFU) to support appropriate medication use. However, challenges such as low health literacy and difficulties navigating these materials may lead to incorrect medication usage, resulting in therapy failure or adverse outcomes. The rise of generative AI, presents an opportunity to provide scalable, personalized patient education through image recognition and text generation. ObjectiveThis study aimed to evaluate the accuracy and safety of medication instructions generated by ChatGPT based on user-provided drug images, compared to the manufacturer's standard instructions. MethodsImages of 12 medications requiring multiple steps for administration were uploaded to ChatGPT's image recognition function. ChatGPT's responses were compared to the official IFU and MG using text classifiers, Count Vectorization (CountVec), and Term Frequency-Inverse Document Frequency (TF-IDF). The clinical accuracy was further evaluated by independent pharmacists to determine if ChatGPT responses were valid for patient instruction. ResultsChatGPT correctly identified all medications and generated patient instructions. CountVec outperformed TF-IDF in text similarity analysis, with an average similarity score of 76%. However, clinical evaluation revealed significant gaps in the instructions, particularly for complex administration routes, where ChatGPT's guidance lacked essential details, leading to lower clinical accuracy scores. ConclusionWhile ChatGPT shows promise in generating patient-friendly medication instructions, its effectiveness varies based on the complexity of the medication. The findings underscore the need for further refinement and clinical oversight to ensure the safety and accuracy of AI-generated medical guidance, particularly for medications with complex administration processes.

Acupressure On Chemotherapy-Induced Nausea and Vomiting among Breast Cancer Patients: A Systematic Review and Meta-analysis.

Nausea and vomiting are one of the common and distressing side effects of chemotherapy in breast cancer patients often impacting their quality of life and treatment adherence. The purpose of this systematic review and meta-analysis was to determine whether acupressure is effective in treating breast cancer patients' acute nausea and vomiting brought on by chemotherapy as well as delayed nausea and vomiting. We systematically searched for Randomized controlled trials and quasi-experimental studies in PubMed, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Clinical Key, Web of Science, EMBASE, and Scopus. Based on the inclusion criteria two reviewers independently identified the articles using key thesaurus and free text terms. The review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement. According to the pooled findings, acupressure combined with antiemetics greatly lessens the severity of acute nausea [SMD, (95% CI)] [-0.35(-0.62,-0.08), P=0.01, I2=0%], delayed nausea [SMD, (95% CI)] [-0.52(-0.78,-0.26), P<0.001, I2=16%], and delayed vomiting [SMD, (95% CI)] [-0.46(- 0.83,-0.08), P=0.02, I2=43%] brought on by chemotherapy. For chemotherapy-treated breast cancer patients, acupressure is a helpful complementary therapy for easing nausea and vomiting.

Is artificial intelligence for medical professionals serving the patients?

BackgroundAlgorithmic decision-making (ADM) utilises algorithms to collect and process data and develop models to make or support decisions. Advances in artificial intelligence (AI) have led to the development of support systems that can be superior to medical professionals without AI support in certain tasks. However, whether patients can benefit from this remains unclear. The aim of this systematic review is to assess the current evidence on patient-relevant benefits and harms, such as improved survival rates and reduced treatment-related complications, when healthcare professionals use ADM systems (developed using or working with AI) compared to healthcare professionals without AI-related ADM (standard care)—regardless of the clinical issues.MethodsFollowing the PRISMA statement, MEDLINE and PubMed (via PubMed), Embase (via Elsevier) and IEEE Xplore will be searched using English free text terms in title/abstract, Medical Subject Headings (MeSH) terms and Embase Subject Headings (Emtree fields). Additional studies will be identified by contacting authors of included studies and through reference lists of included studies. Grey literature searches will be conducted in Google Scholar. Risk of bias will be assessed by using Cochrane’s RoB 2 for randomised trials and ROBINS-I for non-randomised trials. Transparent reporting of the included studies will be assessed using the CONSORT-AI extension statement. Two researchers will screen, assess and extract from the studies independently, with a third in case of conflicts that cannot be resolved by discussion.DiscussionIt is expected that there will be a substantial shortage of suitable studies that compare healthcare professionals with and without ADM systems concerning patient-relevant endpoints. This can be attributed to the prioritisation of technical quality criteria and, in some cases, clinical parameters over patient-relevant endpoints in the development of study designs. Furthermore, it is anticipated that a significant portion of the identified studies will exhibit relatively poor methodological quality and provide only limited generalisable results.Systematic review registrationThis study is registered within PROSPERO (CRD42023412156).

Authentic interpretation: debatable issues of theory

The article is devoted to the study of the legal nature and historical origins of authentic interpretation, as well as the analysis of its practical necessity at the current stage of the development of the legal system, taking into account foreign experience. It was found that in the Enlightenment era, judicial interpretation was subjected to considerable criticism due to the lack of legal certainty, it was considered as a distortion of the text of the law. Later, the reflection of the significance of the authority of the subject of creating legal norms for public interests was manifested in the doctrinal (including the Soviet) understanding of interpretation as a process of clarifying the will and intentions of the legislator. The author found that the most widespread in domestic jurisprudence is the approach according to which the authentic interpretation is considered as a type of official interpretation issued by the body that issued the interpreted norm. However, the author justified that in modern conditions this approach does not correspond to the latest methodological basis of legal interpretation, as it does not take into account the coordinates of social values, the results of the application of the legal norm (its social effect) and, accordingly, the possibility of dynamic interpretation. Conclusions are made about the justification of authentic interpretation when clarifying the content of contracts, agreements, including international ones, when the will of the parties at the time of concluding these acts is of primary importance. It is emphasized that the explanations of law-making subjects regarding the specifics of the application of this or that normative legal act (legal prescription) may have a recommendatory nature. The article emphasizes that the presence of an independent professional subject of interpretation in the person of judges, firstly, disciplines the legislator regarding the strict observance of the rules of legal technique and the minimization of gaps, inaccuracies and ambiguous terms in legal texts; secondly, it is the judges who have the necessary level of expertise and training to apply all modern methods and approaches of legal interpretation to choose the interpretation option most appropriate to public values and social context in a specific case. The importance of establishing at the level of legal regulation the authority of bodies (their structural subdivisions) regarding authentic interpretation, types and legal procedure for the adoption of relevant interpretative acts is asserted. Key words: authentic interpretation; official interpretation; subjects of interpretation; interpretive norms.

Nietzsche, Nishitani, and Laruelle on Faith and Immanence

Abstract This article explores the use of the concept of “faith” in three non-Christian philosophers. The study begins with Nietzsche, who, while deeply critical of Christian belief throughout his work, offers a positive reformulation of the term in a few key texts. From here, the discussion proceeds to two authors who are deeply influenced by Nietzsche, François Laruelle, and Nishitani Keiji. Laruelle’s recent turn to non-theology sees him engaging directly with Christian theological material and presenting a distinction between a positive form of “faith” in contrast from standard religious “belief,” a distinction I suggest bears close resemblance to Nietzsche’s approach, especially in relation to the Apostle Paul. Finally, Nishitani offers his own account of faith, one inspired primarily by the Buddhist notion of faith, but also referencing Christian theology and specifically the practice of Paul, while also connecting with Nietzsche. The connecting theme for all three thinkers is rooted in Zarathustra’s encouragement to be “faithful to the earth,” a non-transcendent, immanent formulation of faith. Faith, in Nishitani and Laruelle especially, is non-doctrinal, non-dogmatic, and non-intellectual; it is, instead, practical, an immanent existence, a way of life resulting in a different form of connection with the world around us.

How the Terms “Spirituality” and “Secularism” Appeared and Have Worked in Modern India

This paper examines the usage of English terms related to the important religious concepts of “spirituality” and “secularism” in and around modern India, employing the simple DH (Digital Humanities) approach of “counting.” The seemingly opposite terms “spirituality” and “secularism” are both essential key notions for the religiosity of the modern world and India, particularly. Like opposite sides of the same coin, they form a conceptual pair that expresses modern universalism and have functioned to mediate and bridge differences in culture and values. Despite the importance, however, scholars have yet to examine how and when the terms themselves have been used thoroughly. This paper explores the usage of these terms in some English-language texts in and around modern India, focusing on the changes in the frequency of their use in the online databases of the Complete Works of Swami Vivekananda and the Times of India. These examinations show that these English words were used in more unique and active ways in India than is often assumed. The modern use of these terms was not necessarily due to Western influence but was, at least partly, developed by modern Indians. In some cases, the Indian usage may have even preceded and influenced the new appearance of these terms in the West. This paper suggests that what we perceive as “modern” is at least partly the product of the agency and participation of the non-Western world, including India.

Keyphrase Extraction from Scientific Articles

Keyphrase extraction is a crucial task in natural language processing (NLP) that involves identifying important terms and phrases in a text. This paper presents a methodology for extracting keyphrases from scientific articles using a combination of preprocessing techniques and the term frequency-inverse document frequency (TF-IDF) algorithm. The approach includes tokenization, stopword removal, and punctuation elimination, followed by the application of the TF-IDF vectorizer to identify and score keyphrases. The results demonstrate the effectiveness of the method in highlighting significant terms in scientific texts.

Petrified and Updated, or How the Interpretive Community Exercises Power Over the Meaning of Vague Terms in the Legal Text (on the Example of Polish Criminal Law)

Petrified and Updated, or How the Interpretive Community Exercises Power Over the Meaning of Vague Terms in the Legal Text (on the Example of Polish Criminal Law)

Digital versus Manual Tracing in Cephalometric Analysis: A Systematic Review and Meta-Analysis.

Background: Over the years, various researchers have attempted to compare digital cephalometry with the conventional manual approach. There is a need to comprehensively analyze the findings from the earlier studies and determine the potential advantages and limitations of each method. The present systematic review aimed to compare the accuracy of digital and manual tracing in cephalometric analysis for the identification of skeletal and dental landmarks. Methods: A systematic search was performed using the keywords "Digital" AND "Manual" AND "Cephalometry" to identify relevant studies published in the English language in the past decade. The electronic data resources consulted for the elaborate search included the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, CINAHL, EMBASE, PsycINFO, Scopus, ERIC, and ScienceDirect with controlled vocabulary and free text terms. Results: A total of n = 20 studies were identified that fulfilled the inclusion and exclusion criteria within the timeframe of 2013 to 2023. The data extracted from the included articles and corresponding meta-analyses are presented in the text. Conclusions: The findings of the present systematic review and meta-analysis revealed trends suggesting that digital tracing may offer reliable measurements for specific cephalometric parameters efficiently and accurately. Orthodontists must consider the potential benefits of digital cephalometry, including time-saving and user-friendliness.

Effects of long and short ejaculatory abstinence on sperm parameters: a meta-analysis of randomized-controlled trials.

This study aimed to investigate the effects of ejaculatory abstinence on sperm parameters. This analysis was registered in PROSPERO (CRD42023472124). We performed a search on PubMed using the following text terms: (("sperm parameters" OR "sperm analysis" [Mesh]) AND ("sperm DNA fragmentation" OR "DNA fragmentation" [Mesh]) AND ("sexual abstinence" [Mesh] OR "abstinence")) and an advanced search in Scopus using the terms ("sperm parameters" OR "sperm parameters" OR "DNA fragmentation") AND ("abstinence"). The sperm parameters that were investigated were sperm volume, total sperm motility, progressive sperm motility, sperm concentration, sperm morphology, and sperm DNA fragmentation (SDF). A two-day cut-off as a "short" or "long" abstinence period has been defined. Thirteen studies published between 2013 and 2022 were included in this meta-analysis. A total of 2,315 patients, ranging from 6 to 836 from each cohort, were enrolled in the study. We showed that longer abstinence time was associated with greater sperm concentration (mean difference [MD]: 8.19; p <0.01), sperm volume (MD: 0.96; p <0.01), and higher SDF (MD: 3.46; p <0.01), but lower progressive sperm motility (MD: -1.83; p <0.01). Otherwise, no statistically significant difference was observed in patients with longer vs. shorter abstinence times regarding total sperm motility (MD: -1.83; p = 0.06). Meta-regression analysis showed that days of abstinence were positively and linearly related to sperm concentration (slope: 3.74; p <0.01) and SDF (slope: 0.65; p = 0.044). According to our data, short ejaculatory abstinence is associated with better sperm quality. Indeed, a higher percentage of progressive sperm motility and lower levels of SDF have been reported in a short abstinence cohort. In contrast, the long abstinence group reported a higher sperm concentration. https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023472124.

Incidence of hand and wrist disorders in primary care.

The incidence of different types of hand and wrist disorders in primary care is unknown since there are no specific encodings for it. To determine the overall incidence and the incidence of specific types of hand and wrist disorders in primary care. A healthcare registration database from Dutch general practice, which contains medical records of over 200 000 patients and included approximately 25% of the population of the area of Rotterdam. Patients aged ≥18 years with a new diagnosis of hand or wrist disorder from 1 January 2015 to 31 December 2019 were extracted using a search algorithm based on ICPC coding and search terms in free text. The mean incidence over the study period of a hand disorder was 5.9 per 1,000 persons-years and of a wrist disorder 0.3 per 1,000 persons-years. The incidence of trigger finger/thumb, fracture hand/finger, tendon/ligament tendinopathy, mallet finger and ligament injury hand/finger were 3 (2.69-3.15), 1 (1.03-1.33), 1 (0.98-1.28), 0.6 (0.48-0.69) and 0.1 (0.06-0.14) per 1,000 persons-years, respectively. The incidence of a wrist fracture and ligament injury were 0.2 (0.13-0.25) and 0.1 (0.04-0.12) per 1,000 persons-years, respectively. There is a large difference between the number of patients presenting to the GP with hand and wrist complaints and the number of hand and wrist diagnosis reported in the medical files. Introducing specific ICPC codes for different types of hand and wrist disorders could (potentially) lead to a more accurate registration of a diagnosis and determination of the incidence figures.