Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptides.

With their diverse biological activities, peptides are promising candidates for therapeutic applications, showing antimicrobial, antitumour and hormonal signalling capabilities. Despite their advantages, therapeutic peptides face challenges such as short half-life, limited oral bioavailability and susceptibility to plasma degradation. The rise of computational tools and artificial intelligence (AI) in peptide research has spurred the development of advanced methodologies and databases that are pivotal in the exploration of these complex macromolecules. This perspective delves into integrating AI in peptide development, encompassing classifier methods, predictive systems and the avant-garde design facilitated by deep-generative models like generative adversarial networks and variational autoencoders. There are still challenges, such as the need for processing optimization and careful validation of predictive models. This work outlines traditional strategies for machine learning model construction and training techniques and proposes a comprehensive AI-assisted peptide design and validation pipeline. The evolving landscape of peptide design using AI is emphasized, showcasing the practicality of these methods in expediting the development and discovery of novel peptides within the context of peptide-based drug discovery.

Bronchioalveolar organoids: A preclinical tool to screen toxicity associated with antibody-drug conjugates.

Despite extensive preclinical testing, cancer therapeutics can result in unanticipated toxicity to non-tumor tissue in patients. These toxicities may pass undetected in preclinical experiments due to modeling limitations involving poor biomimicry of 2-dimensional in vitro cell cultures and due to lack of interspecies translatability in in vivo studies. Instead, primary cells can be grown into miniature 3-dimensional structures that recapitulate morphological and functional aspects of native tissue, termed "organoids." Here, human bronchioalveolar organoids grown from primary alveolar epithelial cells were employed to model lung epithelium and investigate off-target toxicities associated with antibody-drug conjugates (ADCs). ADCs with three different linker-payload combinations (mafodotin, vedotin, and deruxtecan) were tested in bronchioalveolar organoids generated from human, rat, and nonhuman primate lung cells. Organoids demonstrated antibody uptake and changes in viability in response to ADC exposure that model in vivo drug sensitivity. RNA sequencing identified inflammatory activation in bronchioalveolar cells in response to deruxtecan. Future studies will explore specific cell populations involved in interstitial lung disease and incorporate immune cells to the culture.

Dynamic evolution of size and colour in the highly specialized Zodarion ant-eating spiders.

Ecological specialists constitute relevant case studies for understanding the mechanisms, potential and limitations of evolution. The species-rich and strictly myrmecophagous spiders of the genus Zodarion show diversified defence mechanisms, including myrmecomorphy of different ant species and nocturnality. Through Hybridization Capture Using RAD Probes (hyRAD), a phylogenomic technique designed for sequencing poorly preserved specimens, we reconstructed a phylogeny of Zodarion using 52 (approx. a third of the nominal) species that cover its phylogenetic and distributional diversity. We then estimated the evolution of body size and colour, traits that have diversified noticeably and are linked to defence mechanisms, across the group. Our genomic matrix of 300 loci led to a well-supported phylogenetic hypothesis that uncovered two main clades inside Zodarion. Ancestral state estimation revealed the highly dynamic evolution of body size and colour across the group, with multiple transitions and convergences in both traits, which we propose is likely indicative of multiple transitions in ant specialization across the genus. Our study will allow the informed targeted selection of Zodarion taxa of special interest for research into the group's remarkable adaptations to ant specialization. It also exemplifies the utility of hyRAD for phylogenetic studies using museum material.

Gene flow assessment helps to distinguish strong genomic structure from speciation in an Iberian ant-eating spider.

Although genomic data is boosting our understanding of evolution, we still lack a solid framework to perform reliable genome-based species delineation. This problem is especially critical in the case of phylogeographically structured organisms, with allopatric populations showing similar divergence patterns as species. Here, we assess the species limits and phylogeography of Zodarion alacre, an ant-eating spider widely distributed across the Iberian Peninsula. We first performed species delimitation based on genome-wide data and then validated these results using additional evidence. A commonly employed species delimitation strategy detected four distinct lineages with almost no admixture, which present allopatric distributions. These lineages showed ecological differentiation but no clear morphological differentiation, and evidence of introgression in a mitochondrial barcode. Phylogenomic networks found evidence of substantial gene flow between lineages. Finally, phylogeographic methods highlighted remarkable isolation by distance and detected evidence of range expansion from south-central Portugal to central-north Spain. We conclude that despite their deep genomic differentiation, the lineages of Z. alacre do not show evidence of complete speciation. Our results likely shed light on why Zodarion is among the most diversified spider genera despite its limited distribution and support the use of gene flow evidence to inform species boundaries.

Cryptic diversity of Crocidura shrews in the savannahs of Eastern and Southern Africa.

Crocidura (Eulipotyphla, Soricidae) is the most species-rich genus among mammals, with high cryptic diversity and complicated taxonomy. The hirta-flavescens group of Crocidura represents the most abundant and widespread shrews in savannahs of eastern and southern Africa, making them a suitable phylogeographical model for assessing the role of paleoclimatic changes on current biodiversity in open African habitats. We present the first comprehensive study on the phylogeography, evolutionary history, geographical distribution, systematics, and taxonomy of the group, using the integration of mitochondrial, genome-wide (ddRAD sequencing), morphological and morphometrical data collected from specimens over most of the known geographic distribution. Our genomic data confirmed the monophyly of this group and its sister relationship with the olivieri group of Crocidura. There is a substantial genetic variation within the hirta-flavescens group, with three highly supported clades showing parapatric distribution and which can be distinguished morphologically: C. hirta, distributed in both the Zambezian and Somali-Masai bioregions, C. flavescens, known from South Africa and south-western Zambia, and C. cf. flavescens, which is known to occur only in central and western Tanzania. Morphometric data revealed relatively minor differences between C. hirta and C. cf. flavescens, but they differ in the colouration of the pelage. Diversification of the hirta-flavescens group has most likely happened during phases of grassland expansion and contraction during Plio-Pleistocene climatic cycles. Eastern African Rift system, rivers, and the distinctiveness of Zambezian and Somali-Masai bioregions seem to have also shaped the pattern of their diversity, which is very similar to sympatric rodent species living in open habitats. Finally, we review the group's taxonomy and propose to revalidate C. bloyeti, currently a synonym of C. hirta, including the specimens treated as C. cf. flavescens.

Stratification of lymph node metastases as macrometastases, micrometastases, or isolated tumor cells has no clinical implication in patients with cervical cancer: Subgroup analysis of the SCCAN project.

BACKGROUND: In cervical cancer, presence of lymph-node macrometastases (MAC) is a major prognostic factor and an indication for adjuvant treatment. However, since clinical impact of micrometastases (MIC) and isolated tumor-cells (ITC) remains controversial, we sought to identify a cut-off value for the metastasis size not associated with negative prognosis. METHODS: We analyzed data from 967 cervical cancer patients (T1a1L1-T2b) registered in the SCCAN (Surveillance in Cervical CANcer) database, who underwent primary surgical treatment, including sentinel lymph-node (SLN) biopsy with pathological ultrastaging. The size of SLN metastasis was considered a continuous variable and multiple testing was performed for cut-off values of 0.01-1.0 mm. Disease-free survival (DFS) was compared between N0 and subgroups of N1 patients defined by cut-off ranges. RESULTS: LN metastases were found in 172 (18%) patients, classified as MAC, MIC, and ITC in 79, 54, and 39 patients, respectively. DFS was shorter in patients with MAC (HR 2.20, P = 0.003) and MIC (HR 2.87, P < 0.001), while not differing between MAC/MIC (P = 0.484). DFS in the ITC subgroup was neither different from N0 (P = 0.127) nor from MIC/MAC subgroups (P = 0.449). Cut-off analysis revealed significantly shorter DFS compared to N0 in all subgroups with metastases ≥0.4 mm (HR 2.311, P = 0.04). The significance of metastases <0.4 mm could not be assessed due to limited statistical power (<80%). We did not identify any cut-off for the size of metastasis with significantly better prognosis than the rest of N1 group. CONCLUSIONS: In cervical cancer patients, the presence of LN metastases ≥0.4 mm was associated with a significant negative impact on DFS and no cut-off value for the size of metastasis with better prognosis than N1 was found. Traditional metastasis stratification based on size has no clinical implication.

Role of adjuvant therapy in intermediate-risk cervical cancer patients - Subanalyses of the SCCAN study.

OBJECTIVE: The "intermediate-risk" (IR) group of early-stage cervical cancer patients is characterized by negative pelvic lymph nodes and a combination of tumor-related prognostic risk factors such as tumor size ≥2 cm, lymphovascular space invasion (LVSI), and deep stromal invasion. However, the role of adjuvant treatment in these patients remains controversial. We investigated whether adjuvant (chemo)radiation is associated with a survival benefit after radical surgery in patients with IR cervical cancer. METHODS: We analyzed data from patients with IR cervical cancer (tumor size 2-4 cm plus LVSI OR tumor size >4 cm; N0; no parametrial invasion; clear surgical margins) who underwent primary curative-intent surgery between 2007 and 2016 and were retrospectively registered in the international multicenter Surveillance in Cervical CANcer (SCCAN) study. RESULTS: Of 692 analyzed patients, 274 (39.6%) received no adjuvant treatment (AT-) and 418 (60.4%) received radiotherapy or chemoradiotherapy (AT+). The 5-year disease-free survival (83.2% and 80.3%; PDFS = 0.365) and overall survival (88.7% and 89.0%; POS = 0.281) were not significantly different between the AT- and AT+ groups, respectively. Adjuvant (chemo)radiotherapy was not associated with a survival benefit after adjusting for confounding factors by case-control propensity score matching or in subgroup analyses of patients with tumor size ≥4 cm and <4 cm. In univariable analysis, adjuvant (chemo)radiotherapy was not identified as a prognostic factor in any of the subgroups (full cohort: PDFS = 0.365; POS = 0.282). CONCLUSION: Among patients with IR early-stage cervical cancer, radical surgery alone achieved equal disease-free and overall survival rates to those achieved by combining radical surgery with adjuvant (chemo)radiotherapy.

Survival associated with extent of radical hysterectomy in early-stage cervical cancer: a subanalysis of the Surveillance in Cervical CANcer (SCCAN) collaborative study.

BACKGROUND: International guidelines recommend tailoring the radicality of hysterectomy according to the known preoperative tumor characteristics in patients with early-stage cervical cancer. OBJECTIVE: This study aimed to assess whether increased radicality had an effect on 5-year disease-free survival in patients with early-stage cervical cancer undergoing radical hysterectomy. The secondary aims were 5-year overall survival and pattern of recurrence. STUDY DESIGN: This was an international, multicenter, retrospective study from the Surveillance in Cervical CANcer (SCCAN) collaborative cohort. Patients with the International Federation of Gynecology and Obstetrics 2009 stage IB1 and IIA1 who underwent open type B/C1/C2 radical hysterectomy according to Querleu-Morrow classification between January 2007 and December 2016, who did not undergo neoadjuvant chemotherapy and who had negative lymph nodes and free surgical margins at final histology, were included. Descriptive statistics and survival analyses were performed. Patients were stratified according to pathologic tumor diameter. Propensity score match analysis was performed to balance baseline characteristics in patients undergoing nerve-sparing and non-nerve-sparing radical hysterectomy. RESULTS: A total of 1257 patients were included. Of note, 883 patients (70.2%) underwent nerve-sparing radical hysterectomy, and 374 patients (29.8%) underwent non-nerve-sparing radical hysterectomy. Baseline differences between the study groups were found for tumor stage and diameter (higher use of non-nerve-sparing radical hysterectomy for tumors >2 cm or with vaginal involvement; P<.0001). The use of adjuvant therapy in patients undergoing nerve-sparing and non-nerve-sparing radical hysterectomy was 27.3% vs 28.6%, respectively (P=.63). Five-year disease-free survival in patients undergoing nerve-sparing vs non-nerve-sparing radical hysterectomy was 90.1% (95% confidence interval, 87.9-92.2) vs 93.8% (95% confidence interval, 91.1-96.5), respectively (P=.047). Non-nerve-sparing radical hysterectomy was independently associated with better disease-free survival at multivariable analysis performed on the entire cohort (hazard ratio, 0.50; 95% confidence interval, 0.31-0.81; P=.004). Furthermore, 5-year overall survival in patients undergoing nerve-sparing vs non-nerve-sparing radical hysterectomy was 95.7% (95% confidence interval, 94.1-97.2) vs non-nerve-sparing 96.5% (95% confidence interval, 94.3-98.7), respectively (P=.78). In patients with a tumor diameter ≤20 mm, 5-year disease-free survival was 94.7% in nerve-sparing radical hysterectomy vs 96.2% in non-nerve-sparing radical hysterectomy (P=.22). In patients with tumors between 21 and 40 mm, 5-year disease-free survival was 90.3% in non-nerve-sparing radical hysterectomy vs 83.1% in nerve-sparing radical hysterectomy (P=.016) (no significant difference in the rate of adjuvant treatment in this subgroup, P=.47). This was confirmed after propensity match score analysis (balancing the 2 study groups). The pattern of recurrence in the propensity-matched population did not demonstrate any difference (P=.70). CONCLUSION: For tumors ≤20 mm, no survival difference was found with more radical hysterectomy. For tumors between 21 and 40 mm, a more radical hysterectomy was associated with improved 5-year disease-free survival. No difference in the pattern of recurrence according to the extent of radicality was observed. Non-nerve-sparing radical hysterectomy was associated with better 5-year disease-free survival than nerve-sparing radical hysterectomy after propensity score match analysis.

Factors associated with emergency room readmission after elective surgery for ovarian carcinoma.

BACKGROUND: Hospital readmission is a quality metric of hospital care and has been studied in ovarian carcinoma, but its evaluation has several limitations. Also, emergency room (ER) readmission is considered an adverse effect because it represents patient costs. Therefore, our objective was to determine the rate of ER readmission, its causes, and associated factors. METHODS: A retrospective study of 592 patients with ovarian carcinoma who underwent upfront surgery, neoadjuvant therapy, or surgery for recurrent disease. An analysis of factors associated with ER readmission, hospital readmission, and surgical complications was performed, including multivariate analysis to assess for case-mix factors. RESULTS: Of 592 patients, the median age was 51 years, and the predominant type of treatment was the neoadjuvant approach (52.9%); 46% underwent upfront surgeries and six surgeries for recurrence. The ratio to ER readmission was 11.8% (70 patients), of whom 12 patients were admitted more than once. The factors associated with ER readmission were prolonged surgery, intraoperative bleeding, extended hospital stay, the time of the day when the surgery was performed, and post-surgical complications. The hospital readmissions were 4.2%, and the overall morbidity was 17.6%. In the multivariate analysis, the only factor associated with ER readmission was the presence of surgical complications (OR = 39.01). The factors independently associated with hospital readmission were the entrance to the intensive care unit (OR = 1.37), the presence of surgical complications (OR = 2.85), and ER readmission (OR = 1.45). CONCLUSION: ER readmission is an adverse event representing the presence of symptoms/complications in patients. Evaluating the ER readmission independently of the readmission to the hospital is critical because it will allow modifying medical care behaviors to prevent patients from unnecessarily returning to the hospital after a hospital discharge to manage preventable medical problems. TRIAL REGISTRATION: researchregistry7882.

Dog and Cat Bites: Rapid Evidence Review.

Animal bites are a significant burden to health care systems worldwide. In the United States, dog bites account for an average of 337,000 emergency visits and generate medical costs of up to $2 billion per year. Most animal bites in adults and children are from a dog, and most bite patients are children who have been bitten by animals known to them. Dog bites may cause crush and soft-tissue avulsion, whereas cat bites usually cause deeper puncture-type wounds. Children most often present with dog bites on the head and neck, and adolescents and adults usually present with dog bites on the extremities and hands. Bite wounds should be examined, cleaned, and irrigated with warm water or normal saline solution, and any foreign bodies and devitalized tissue should be removed. Neurovascular function (e.g., pulses, sensation) and range and movement of adjacent joints should be examined and documented. Antibiotic prophylaxis, with amoxicillin/clavulanate as the first-line choice, should be considered for all bites, particularly for those at increased risk of infection. Imaging and laboratory studies are usually not required unless there is suspicion of a retained foreign body, damage to underlying structures, infection, or extensive injury. Primary closure of bite wounds may be performed if there is low risk of infection. The need for tetanus vaccination and rabies postexposure prophylaxis should be evaluated for each patient; bites that do not break the skin generally do not require rabies postexposure prophylaxis.

Knowledge management tools and mechanisms for evidence-informed decision-making in the WHO European Region: a scoping review.

BACKGROUND: Knowledge management (KM) emerged as a strategy to promote evidence-informed decision-making. This scoping review aims to map existing KM tools and mechanisms used to promote evidence-informed health decision-making in the WHO European Region and identify knowledge gaps. METHODS: Following the Joanna Briggs Institute (JBI) guidance for conducting scoping reviews, we searched Medline, PubMed, EMBASE, the Cochrane library, and Open Grey. We conducted a descriptive analysis of the general characteristics of the included papers and conducted narrative analysis of the included studies and categorized studies according to KM type and phase. RESULTS: Out of 9541 citations identified, we included 141 studies. The KM tools mostly assessed are evidence networks, surveillance tools, observatories, data platforms and registries, with most examining KM tools in high-income countries of the WHO European region. Findings suggest that KM tools can identify health problems, inform health planning and resource allocation, increase the use of evidence by policymakers and stimulate policy discussion. CONCLUSION: Policymakers and funding agencies are called to support capacity-building activities, and future studies to strengthen KM in the WHO European region particularly in Eastern Europe and Central Asia. An updated over-arching strategy to coordinate KM activities in the WHO European region will be useful in these efforts.

Power Disturbance Monitoring through Techniques for Novelty Detection on Wind Power and Photovoltaic Generation.

Novelty detection is a statistical method that verifies new or unknown data, determines whether these data are inliers (within the norm) or outliers (outside the norm), and can be used, for example, in developing classification strategies in machine learning systems for industrial applications. To this end, two types of energy that have evolved over time are solar photovoltaic and wind power generation. Some organizations around the world have developed energy quality standards to avoid known electric disturbances; however, their detection is still a challenge. In this work, several techniques for novelty detection are implemented to detect different electric anomalies (disturbances), which are k-nearest neighbors, Gaussian mixture models, one-class support vector machines, self-organizing maps, stacked autoencoders, and isolation forests. These techniques are applied to signals from real power quality environments of renewable energy systems such as solar photovoltaic and wind power generation. The power disturbances that will be analyzed are considered in the standard IEEE-1159, such as sag, oscillatory transient, flicker, and a condition outside the standard attributed to meteorological conditions. The contribution of the work consists of the development of a methodology based on six techniques for novelty detection of power disturbances, under known and unknown conditions, over real signals in the power quality assessment. The merit of the methodology is a set of techniques that allow to obtain the best performance of each one under different conditions, which constitutes an important contribution to the renewable energy systems.

State of Charge Estimation Model Based on Genetic Algorithms and Multivariate Linear Regression with Applications in Electric Vehicles.

Nowadays, the use of renewable, green/eco-friendly technologies is attracting the attention of researchers, with a view to overcoming recent challenges that must be faced to guarantee the availability of Electric Vehicles (EVs). Therefore, this work proposes a methodology based on Genetic Algorithms (GA) and multivariate regression for estimating and modeling the State of Charge (SOC) in Electric Vehicles. Indeed, the proposal considers the continuous monitoring of six load-related variables that have an influence on the SOC (State of Charge), specifically, the vehicle acceleration, vehicle speed, battery bank temperature, motor RPM, motor current, and motor temperature. Thus, these measurements are evaluated in a structure comprised of a Genetic Algorithm and a multivariate regression model in order to find those relevant signals that better model the State of Charge, as well as the Root Mean Square Error (RMSE). The proposed approach is validated under a real set of data acquired from a self-assembly Electric Vehicle, and the obtained results show a maximum accuracy of approximately 95.5%; thus, this proposed method can be applied as a reliable diagnostic tool in the automotive industry.

A Pathogenic Variant Reclassified to the Pseudogene PMS2P1 in a Patient with Suspected Hereditary Cancer.

The PMS2 gene is involved in DNA repair by the mismatch repair pathway. Deficiencies in this mechanism have been associated with Lynch Syndrome (LS), which is characterized by a high risk for colorectal, endometrial, ovarian, breast, and other cancers. Germinal pathogenic variants of PMS2 are associated with up to 5% of all cases of LS. The prevalence is overestimated for the existence of multiple homologous pseudogenes. We report the case of a 44-year-old woman diagnosed with breast cancer at 34 years without a relevant cancer family history. The presence of pathogenic variant NM_000535.7:c.1A > T, (p.Met1Leu) in PMS2 was determined by next-generation sequencing analysis with a panel of 322 cancer-associated genes and confirmed by capillary sequencing in the patient. The variant was determined in six family members (brothers, sisters, and a son) and seven non-cancerous unrelated individuals. Analysis of the amplified region showed high homology of PMS2 with five of its pseudogenes. We determined that the variant is associated with the PMS2P1 pseudogene following sequence alignment analysis. We propose considering the variant c.1A > T, (p.Met1Leu) in PMS2 for reclassification as not hereditary cancer-related, given the impact on the diagnosis and treatment of cancer patients and families carrying this variant.

An Entropy-Based Condition Monitoring Strategy for the Detection and Classification of Wear Levels in Gearboxes.

Gears are reliable and robust elements that are found in any power transmission system. However, gears are prone to present incipient faults, such as wear, since they are constantly subjected to contact forces. Due to gears playing a key role in many industrial processes, it is important to develop condition monitoring strategies that ensure the proper functioning of the related power transmission system and the overall components. In this regard, the data on entropy provide relevant information that allow us to identify and quantify the effect of different wear levels in gears. Therefore, in this work, we proposed the use of seven entropy-related features to perform the identification of different wear severities in a gearbox. The novelty of this proposal lies in the use of the entropy features to carry out a high-performance characterization of the available vibration signals that are acquired from experimental tests. The novelty of this proposal lies in the fusion of three different techniques: entropy features, linear discriminant analysis, and artificial neural networks to obtain a machine learning approach for improving the detection of different wear severities in gears compared to other reported methodologies. This situation is achieved due to the high-performance characterization of the available vibration signals that are acquired from experimental tests. Additionally, the entropy features are subjected to a feature space transformation by means of linear discriminant analysis to obtain a 2D representation and, finally, the set of features extracted by linear discriminant analysis are used as inputs of a neural network-based classifier to determine the severity of wear that is present in the gears. The proposed methodology is validated and compared with a conventional statistical approach to show the improvement in the classification.

Protein haploinsufficiency drivers identify MYBPC3 variants that cause hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac disease. Variants in MYBPC3, the gene encoding cardiac myosin-binding protein C (cMyBP-C), are the leading cause of HCM. However, the pathogenicity status of hundreds of MYBPC3 variants found in patients remains unknown, as a consequence of our incomplete understanding of the pathomechanisms triggered by HCM-causing variants. Here, we examined 44 nontruncating MYBPC3 variants that we classified as HCM-linked or nonpathogenic according to cosegregation and population genetics criteria. We found that around half of the HCM-linked variants showed alterations in RNA splicing or protein stability, both of which can lead to cMyBP-C haploinsufficiency. These protein haploinsufficiency drivers associated with HCM pathogenicity with 100% and 94% specificity, respectively. Furthermore, we uncovered that 11% of nontruncating MYBPC3 variants currently classified as of uncertain significance in ClinVar induced one of these molecular phenotypes. Our strategy, which can be applied to other conditions induced by protein loss of function, supports the idea that cMyBP-C haploinsufficiency is a fundamental pathomechanism in HCM.

Infodemics and health misinformation: a systematic review of reviews.

Objective: To compare and summarize the literature regarding infodemics and health misinformation, and to identify challenges and opportunities for addressing the issues of infodemics. Methods: We searched MEDLINE®, Embase®, Cochrane Library of Systematic Reviews, Scopus and Epistemonikos on 6 May 2022 for systematic reviews analysing infodemics, misinformation, disinformation and fake news related to health. We grouped studies based on similarity and retrieved evidence on challenges and opportunities. We used the AMSTAR 2 approach to assess the reviews' methodological quality. To evaluate the quality of the evidence, we used the Grading of Recommendations Assessment, Development and Evaluation guidelines. Findings: Our search identified 31 systematic reviews, of which 17 were published. The proportion of health-related misinformation on social media ranged from 0.2% to 28.8%. Twitter, Facebook, YouTube and Instagram are critical in disseminating the rapid and far-reaching information. The most negative consequences of health misinformation are the increase of misleading or incorrect interpretations of available evidence, impact on mental health, misallocation of health resources and an increase in vaccination hesitancy. The increase of unreliable health information delays care provision and increases the occurrence of hateful and divisive rhetoric. Social media could also be a useful tool to combat misinformation during crises. Included reviews highlight the poor quality of published studies during health crises. Conclusion: Available evidence suggests that infodemics during health emergencies have an adverse effect on society. Multisectoral actions to counteract infodemics and health misinformation are needed, including developing legal policies, creating and promoting awareness campaigns, improving health-related content in mass media and increasing people's digital and health literacy.

Data gaps towards health development goals, 47 low- and middle-income countries.

OBJECTIVE: To assess the availability and gaps in data for measuring progress towards health-related sustainable development goals and other targets in selected low- and middle-income countries. METHODS: We used 14 international population surveys to evaluate the health data systems in the 47 least developed countries over the years 2015-2020. We reviewed the survey instruments to determine whether they contained tools that could be used to measure 46 health-related indicators defined by the World Health Organization. We recorded the number of countries with data available on the indicators from these surveys. FINDINGS: Twenty-seven indicators were measurable by the surveys we identified. The two health emergency indicators were not measurable by current surveys. The percentage of countries that used surveys to collect data over 2015-2020 were lowest for tuberculosis (2/47; 4.3%), hepatitis B (3/47; 6.4%), human immunodeficiency virus (11/47; 23.4%), child development status and child abuse (both 13/47; 27.7%), compared with safe drinking water (37/47; 78.7%) and births attended by skilled health personnel (36/47; 76.6%). Nineteen countries collected data on 21 or more indicators over 2015-2020 while nine collected data on no indicators; over 2018-2020 these numbers reduced to six and 20, respectively. CONCLUSION: Examining selected international surveys provided a quick summary of health data available in the 47 least developed countries. We found major gaps in health data due to long survey cycles and lack of appropriate survey instruments. Novel indicators and survey instruments would be needed to track the fast-changing situation of health emergencies.

Post-recurrence survival in patients with cervical cancer.

BACKGROUND: Up to 26% of patients with early-stage cervical cancer experience relapse after primary surgery. However, little is known about which factors influence prognosis following disease recurrence. Therefore, our aims were to determine post-recurrence disease-specific survival (PR-DSS) and to identify respective prognostic factors for PR-DSS. METHODS: Data from 528 patients with early-stage cervical cancer who relapsed after primary surgery performed between 2007 and 2016 were obtained from the SCANN study (Surveillance in Cervical CANcer). Factors related to the primary disease and recurrence were combined in a multivariable Cox proportional hazards model to predict PR-DSS. RESULTS: The 5-year PR-DSS was 39.1% (95% confidence interval [CI] 22.7%-44.5%), median disease-free interval between primary surgery and recurrence (DFI1) was 1.5 years, and median survival after recurrence was 2.5 years. Six significant variables were identified in the multivariable analysis and were used to construct the prognostic model. Two were related to primary treatment (largest tumour size and lymphovascular space invasion) and four to recurrence (DFI1, age at recurrence, presence of symptoms, and recurrence type). The C-statistic after 10-fold cross-validation of prognostic model reached 0.701 (95% CI 0.675-0.727). Three risk-groups with significantly differing prognoses were identified, with 5-year PR-DSS rates of 81.8%, 44.6%, and 12.7%. CONCLUSIONS: We developed the robust model of PR-DSS to stratify patients with relapsed cervical cancer according to risk profiles using six routinely recorded prognostic markers. The model can be utilised in clinical practice to aid decision-making on the strategy of recurrence management, and to better inform the patients.

Phylogenomics and loci dropout patterns of deeply diverged Zodarion ant-eating spiders suggest a high potential of RAD-seq for genus-level spider phylogenetics.

RAD sequencing yields large amounts of genome-wide data at a relatively low cost and without requiring previous taxon-specific information, making it ideal for evolutionary studies of highly diversified and neglected organisms. However, concerns about information decay with phylogenetic distance have discouraged its use for assessing supraspecific relationships. Here, using Double Digest Restriction Associated DNA (ddRAD) data, we perform the first deep-level approach to the phylogeny of Zodarion, a highly diversified spider genus. We explore the impact of loci and taxon filtering across concatenated and multispecies coalescent reconstruction methods and investigate the patterns of information dropout in reference to both the time of divergence and the mitochondrial divergence between taxa. We found that relaxed loci-filtering and nested taxon-filtering strategies maximized the amount of molecular information and improved phylogenetic inference. As expected, there was a clear pattern of allele dropout towards deeper time and mitochondrial divergences, but the phylogenetic signal remained strong throughout the phylogeny. Therefore, we inferred topologies that were almost fully resolved, highly supported, and noticeably congruent between setups and inference methods, which highlights overall inconsistency in the taxonomy of Zodarion. Because Zodarion appears to be among the oldest and most mitochondrially diversified spider genera, our results suggest that ddRAD data show high potential for inferring intra-generic relationships across spiders and probably also in other taxonomic groups.