3D airway geometry analysis of factors in airway navigation failure for lung nodules.

BACKGROUND: This study aimed to quantitatively reveal contributing factors to airway navigation failure during radial probe endobronchial ultrasound (R-EBUS) by using geometric analysis in a three-dimensional (3D) space and to investigate the clinical feasibility of prediction models for airway navigation failure. METHODS: We retrospectively reviewed patients who underwent R-EBUS between January 2017 and December 2018. Geometric quantification was analyzed using in-house software built with open-source python libraries including the Vascular Modeling Toolkit ( http://www.vmtk.org ), simple insight toolkit ( https://sitk.org ), and sci-kit image ( https://scikit-image.org ). We used a machine learning-based approach to explore the utility of these significant factors. RESULTS: Of the 491 patients who were eligible for analysis (mean age, 65 years +/- 11 [standard deviation]; 274 men), the target lesion was reached in 434 and was not reached in 57. Twenty-seven patients in the failure group were matched with 27 patients in the success group based on propensity scores. Bifurcation angle at the target branch, the least diameter of the last section, and the curvature of the last section are the most significant and stable factors for airway navigation failure. The support vector machine can predict airway navigation failure with an average area under the curve of 0.803. CONCLUSIONS: Geometric analysis in 3D space revealed that a large bifurcation angle and a narrow and tortuous structure of the closest bronchus from the lesion are associated with airway navigation failure during R-EBUS. The models developed using quantitative computer tomography scan imaging show the potential to predict airway navigation failure.

Predicting cerebrovascular age and its clinical relevance: Modeling using 3D morphological features of brain vessels.

Aging manifests as many phenotypes, among which age-related changes in brain vessels are important, but underexplored. Thus, in the present study, we constructed a model to predict age using cerebrovascular morphological features, further assessing their clinical relevance using a novel pipeline. Age prediction models were first developed using data from a normal cohort (n = 1181), after which their relevance was tested in two stroke cohorts (n = 564 and n = 455). Our novel pipeline adapted an existing framework to compute generic vessel features for brain vessels, resulting in 126 morphological features. We further built various machine learning models to predict age using only clinical factors, only brain vessel features, and a combination of both. We further assessed deviation from healthy aging using the age gap and explored its clinical relevance by correlating the predicted age and age gap with various risk factors. The models constructed using only brain vessel features and those combining clinical factors with vessel features were better predictors of age than the clinical factor-only model (r = 0.37, 0.48, and 0.26, respectively). Predicted age was associated with many known clinical factors, and the associations were stronger for the age gap in the normal cohort. The age gap was also associated with important factors in the pooled cohort atherosclerotic cardiovascular disease risk score and white matter hyperintensity measurements. Cerebrovascular age, computed using the morphological features of brain vessels, could serve as a potential individualized marker for the early detection of various cerebrovascular diseases.

Recent advances in materials and manufacturing of implantable devices for continuous health monitoring.

Implantable devices are vital in healthcare, enabling continuous monitoring, early disease detection, informed decision-making, enhanced outcomes, cost reduction, and chronic condition management. These devices provide real-time data, allowing proactive healthcare interventions, and contribute to overall improvements in patient care and quality of life. The success of implantable devices relies on the careful selection of materials and manufacturing methods. Recent materials research and manufacturing advancements have yielded implantable devices with enhanced biocompatibility, reliability, and functionality, benefiting human healthcare. This paper provides a comprehensive overview of the latest developments in implantable medical devices, emphasizing the importance of material selection and manufacturing methods, including biocompatibility, self-healing capabilities, corrosion resistance, mechanical properties, and conductivity. It explores various manufacturing techniques such as microfabrication, 3D printing, laser micromachining, electrospinning, screen printing, inkjet printing, and nanofabrication. The paper also discusses challenges and limitations in the field, including biocompatibility concerns, privacy and data security issues, and regulatory hurdles for implantable devices.

Enhancing Identification of High-Risk cN0 Lung Adenocarcinoma Patients Using MRI-Based Radiomic Features.

Purpose: To develop an MRI-based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space (STAS), and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography-CT (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, SUVmax (maximum standardized uptake value) on FDG PET/CT, and the mean ADC value on DWI, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The MR-eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p<0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p<0.001), worse 4-year disease free survival (p<0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC 0.860 and 0.907, respectively). Conclusion: Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.

Gintonin upregulates cytokine production and expression of NKp30, NKp44 and NKp44 related to natural killer cell activity on immunosuppressive rat.

The objective of the study is to estimate the potential of gintonin, as an immune enhancing agent through natural killer cell (NK cell) activity in cyclophosphamide (CY)-induced immunosuppressive animals. Accumulated results reveals that, gintonin attenuated CY-induced immunosuppression and it might modulate NK cell activity to boost the immunity.

Emerging evidence that ginseng components improve cognition in subjective memory impairment, mild cognitive impairment, and early Alzheimer's disease dementia.

Ginseng is a traditional herbal medicine used for prevention and treatment of various diseases as a tonic. Recent scientific cohort studies on life prolongation with ginseng consumption support this record, as those who consumed ginseng for more than 5 years had reduced mortality and cognitive decline compared to those who did not. Clinical studies have also shown that acute or long-term intake of ginseng total extract improves acute working memory performance or cognitive function in healthy individuals and those with subjective memory impairment (SMI), mild cognitive impairment (MCI), or early Alzheimer's disease (AD) dementia who are taking AD medication(s). Ginseng contains various components ranging from classical ginsenosides and polysaccharides to more recently described gintonin. However, it is unclear which ginseng component(s) might be the main candidate that contribute to memory or cognitive improvements or prevent cognitive decline in older individuals. This review describes recent clinical contributors to ginseng components in clinical tests and introduces emerging evidence that ginseng components could be novel candidates for cognitive improvement in older individuals, as ginseng components improve SMI cognition and exhibits add-on effects when co-administered with early AD dementia drugs. The mechanism behind the beneficial effects of ginseng components and how it improves cognition are presented. Additionally, this review shows how ginseng components can contribute to SMI, MCI, or early AD dementia when used as a supplementary food and/or medicine, and proposes a novel combination therapy of current AD medicines with ginseng component(s).

hiPSC-derived macrophages improve drug sensitivity and selectivity in a macrophage-incorporating organoid culture model.

Accurate simulation of different cell type interactions is crucial for physiological and precisein vitrodrug testing. Human tissue-resident macrophages are critical for modulating disease conditions and drug-induced injuries in various tissues; however, their limited availability has hindered their use inin vitromodeling. Therefore, this study aimed to create macrophage-containing organoid co-culture models by directly incorporating human-induced pluripotent stem cell (hiPSC)-derived pre-macrophages into organoid and scaffold cell models. The fully differentiated cells in these organoids exhibited functional characteristics of tissue-resident macrophages with enriched pan-macrophage markers and the potential for M1/M2 subtype specialization upon cytokine stimulation. In a hepatic organoid model, the integrated macrophages replicated typical intrinsic properties, including cytokine release, polarization, and phagocytosis, and the co-culture model was more responsive to drug-induced liver injury than a macrophage-free model. Furthermore, alveolar organoid models containing these hiPSC-derived macrophages also showed increased drug and chemical sensitivity to pulmonary toxicants. Moreover, 3D adipocyte scaffold models incorporating macrophages effectively simulated in vivo insulin resistance observed in adipose tissue and showed improved insulin sensitivity on exposure to anti-diabetic drugs. Overall, the findings demonstrated that incorporating hiPSC-derived macrophages into organoid culture models resulted in more physiological and sensitivein vitrodrug evaluation and screening systems.

Medium-Sized Ring Expansion Strategies: Enhancing Small-Molecule Library Development.

The construction of a small molecule library that includes compounds with medium-sized rings is increasingly essential in drug discovery. These compounds are essential for identifying novel therapeutic agents capable of targeting "undruggable" targets through high-throughput and high-content screening, given their structural complexity and diversity. However, synthesizing medium-sized rings presents notable challenges, particularly with direct cyclization methods, due to issues such as transannular strain and reduced degrees of freedom. This review presents an overview of current strategies in synthesizing medium-sized rings, emphasizing innovative approaches like ring-expansion reactions. It highlights the challenges of synthesis and the potential of these compounds to diversify the chemical space for drug discovery, underscoring the importance of medium-sized rings in developing new bioactive compounds.

Examining geospatial and temporal distribution of invasive non-typhoidal Salmonella disease occurrence in sub-Saharan Africa: a systematic review and modelling study.

BACKGROUND: Invasive non-typhoidal Salmonella (iNTS) disease is a significant health concern in sub-Saharan Africa. While our knowledge of a larger-scale variation is growing, understanding of the subnational variation in iNTS disease occurrence is lacking, yet crucial for targeted intervention. METHOD: We performed a systematic review of reported occurrences of iNTS disease in sub-Saharan Africa, consulting literature from PubMed, Embase and Web of Science published since 2000. Eligibility for inclusion was not limited by study type but required that studies reported original data on human iNTS diseases based on the culture of a normally sterile site, specifying subnational locations and the year, and were available as full-text articles. We excluded studies that diagnosed iNTS disease based on clinical indications, cultures from non-sterile sites or serological testing. We estimated the probability of occurrence of iNTS disease for sub-Saharan Africa on 20 km × 20 km grids by exploring the association with geospatial covariates such as malaria, HIV, childhood growth failure, access to improved water, and sanitation using a boosted regression tree. RESULTS: We identified 130 unique references reporting human iNTS disease in 21 countries published from 2000 through 2020. The estimated probability of iNTS occurrence grids showed significant spatial heterogeneity at all levels (20 km × 20 km grids, subnational, country and subregional levels) and temporal heterogeneity by year. For 2020, the probability of occurrence was higher in Middle Africa (0.34, 95% CI: 0.25 to 0.46), followed by Western Africa (0.33, 95% CI: 0.23 to 0.44), Eastern Africa (0.24, 95% CI: 0.17 to 0.33) and Southern Africa (0.08, 95% CI: 0.03 to 0.11). Temporal heterogeneity indicated that the probability of occurrence increased between 2000 and 2020 in countries such as the Republic of the Congo (0.05 to 0.59) and Democratic Republic of the Congo (0.10 to 0.48) whereas it decreased in countries such as Uganda (0.65 to 0.23) or Zimbabwe (0.61 to 0.37). CONCLUSION: The iNTS disease occurrence varied greatly across sub-Saharan Africa, with certain regions being disproportionately affected. Exploring regions at high risk for iNTS disease, despite the limitations in our data, may inform focused resource allocation. This targeted approach may enhance efforts to combat iNTS disease in more affected areas.

Split Proteins and Reassembly Modules for Biological Applications.

Split systems, modular entities enabling controlled biological processes, have become instrumental in biological research. This review highlights their utility across applications like gene regulation, protein interaction identification, and biosensor development. Covering significant progress over the last decade, it revisits traditional split proteins such as GFP, luciferase, and inteins, and explores advancements in technologies like Cas proteins and base editors. We also examine reassembly modules and their applications in diverse fields, from gene regulation to therapeutic innovation. This review offers a comprehensive perspective on the recent evolution of split systems in biological research.

Estimating the health effects of COVID-19-related immunisation disruptions in 112 countries during 2020-30: a modelling study.

BACKGROUND: There have been declines in global immunisation coverage due to the COVID-19 pandemic. Recovery has begun but is geographically variable. This disruption has led to under-immunised cohorts and interrupted progress in reducing vaccine-preventable disease burden. There have, so far, been few studies of the effects of coverage disruption on vaccine effects. We aimed to quantify the effects of vaccine-coverage disruption on routine and campaign immunisation services, identify cohorts and regions that could particularly benefit from catch-up activities, and establish if losses in effect could be recovered. METHODS: For this modelling study, we used modelling groups from the Vaccine Impact Modelling Consortium from 112 low-income and middle-income countries to estimate vaccine effect for 14 pathogens. One set of modelling estimates used vaccine-coverage data from 1937 to 2021 for a subset of vaccine-preventable, outbreak-prone or priority diseases (ie, measles, rubella, hepatitis B, human papillomavirus [HPV], meningitis A, and yellow fever) to examine mitigation measures, hereafter referred to as recovery runs. The second set of estimates were conducted with vaccine-coverage data from 1937 to 2020, used to calculate effect ratios (ie, the burden averted per dose) for all 14 included vaccines and diseases, hereafter referred to as full runs. Both runs were modelled from Jan 1, 2000, to Dec 31, 2100. Countries were included if they were in the Gavi, the Vaccine Alliance portfolio; had notable burden; or had notable strategic vaccination activities. These countries represented the majority of global vaccine-preventable disease burden. Vaccine coverage was informed by historical estimates from WHO-UNICEF Estimates of National Immunization Coverage and the immunisation repository of WHO for data up to and including 2021. From 2022 onwards, we estimated coverage on the basis of guidance about campaign frequency, non-linear assumptions about the recovery of routine immunisation to pre-disruption magnitude, and 2030 endpoints informed by the WHO Immunization Agenda 2030 aims and expert consultation. We examined three main scenarios: no disruption, baseline recovery, and baseline recovery and catch-up. FINDINGS: We estimated that disruption to measles, rubella, HPV, hepatitis B, meningitis A, and yellow fever vaccination could lead to 49 119 additional deaths (95% credible interval [CrI] 17 248-134 941) during calendar years 2020-30, largely due to measles. For years of vaccination 2020-30 for all 14 pathogens, disruption could lead to a 2·66% (95% CrI 2·52-2·81) reduction in long-term effect from 37 378 194 deaths averted (34 450 249-40 241 202) to 36 410 559 deaths averted (33 515 397-39 241 799). We estimated that catch-up activities could avert 78·9% (40·4-151·4) of excess deaths between calendar years 2023 and 2030 (ie, 18 900 [7037-60 223] of 25 356 [9859-75 073]). INTERPRETATION: Our results highlight the importance of the timing of catch-up activities, considering estimated burden to improve vaccine coverage in affected cohorts. We estimated that mitigation measures for measles and yellow fever were particularly effective at reducing excess burden in the short term. Additionally, the high long-term effect of HPV vaccine as an important cervical-cancer prevention tool warrants continued immunisation efforts after disruption. FUNDING: The Vaccine Impact Modelling Consortium, funded by Gavi, the Vaccine Alliance and the Bill & Melinda Gates Foundation. TRANSLATIONS: For the Arabic, Chinese, French, Portguese and Spanish translations of the abstract see Supplementary Materials section.

Postbiotic potential of Bacillus velezensis KMU01 cell-free supernatant for the alleviation of obesity in mice.

Attention toward the preventive effects of postbiotics on metabolic diseases has increased because of greater stability and safety over probiotics. However, studies regarding the bioactive effects of postbiotics, especially from probiotic Bacillus strains, are relatively limited. The anti-obesity effects of the cell-free culture supernatant of Bacillus velezensis KMU01 (CFS-B.vele) were evaluated using high-fat-diet (HFD)-induced mice. HFD-induced mice (n = 8 per group) received equal volumes of (1) CFS-B.vele (114 mg/kg) in PBS, (2) Xenical in PBS, or (3) PBS alone by oral gavage daily for 13 weeks. The results demonstrated that CFS-B.vele changed the gut microbiota and showed anti-obesity effects in HFD-induced obese mice. The elevated Firmicutes/Bacteroidota ratio induced by HFD was decreased in the CFS-B.vele group compared to the other groups (p < 0.05). The CFS-B.vele intervention led to the enrichment of SCFA-producers, such as Roseburia and Eubacterium, in the cecum, suggesting their potential involvement in the amelioration of obesity. Due to these changes, the various obesity-related biomarkers (body weight, fat in tissue, white adipose tissue weight and size, serum LDL-cholesterol level, hepatic lipid accumulation, and adipogenesis/lipogenesis-related gene/protein expression) were improved. Our findings suggest that CFS-B.vele has potential as a novel anti-obesity agent through modulation of the gut microbiota.

Ginseng and ginsenosides on cardiovascular and pulmonary diseases; Pharmacological potentials for the coronavirus (COVID-19).

Since its outbreak in late 2019, the Coronavirus disease 2019 (COVID-19) pandemic has profoundly caused global morbidity and deaths. The COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has major complications in cardiovascular and pulmonary system. The increased rate of mortality is due to delayed detection of certain biomarkers that are crucial in the development of disease. Furthermore, certain proteins and enzymes in cellular signaling pathways play an important role in replication of SARS-CoV-2. Most cases are mild to moderate symptoms, however severe cases of COVID-19 leads to death. Detecting the level of biomarkers such as C-reactive protein, cardiac troponin, creatine kinase, creatine kinase-MB, procalcitonin and Matrix metalloproteinases helps in early detection of the severity of disease. Similarly, through downregulating Renin-angiotensin system, interleukin, Mitogen-activated protein kinases and Phosphoinositide 3-kinases pathways, COVID-19 can be effectively controlled and mortality could be prevented. Ginseng and ginsenosides possess therapeutic potential in cardiac and pulmonary complications, there are several studies performed in which they have suppressed these biomarkers and downregulated the pathways, thereby inhibiting the further spread of disease. Supplementation with ginseng or ginsenoside could act on multiple pathways to reduce the level of biomarkers significantly and alleviate cardiac and pulmonary damage. Therefore, this review summarizes the potential of ginseng extract and ginsenosides in controlling the cardiovascular and pulmonary diseases by COVID-19.

Enhancing deep learning classification performance of tongue lesions in imbalanced data: mosaic-based soft labeling with curriculum learning.

BACKGROUND: Oral potentially malignant disorders (OPMDs) are associated with an increased risk of cancer of the oral cavity including the tongue. The early detection of oral cavity cancers and OPMDs is critical for reducing cancer-specific morbidity and mortality. Recently, there have been studies to apply the rapidly advancing technology of deep learning for diagnosing oral cavity cancer and OPMDs. However, several challenging issues such as class imbalance must be resolved to effectively train a deep learning model for medical imaging classification tasks. The aim of this study is to evaluate a new technique of artificial intelligence to improve the classification performance in an imbalanced tongue lesion dataset. METHODS: A total of 1,810 tongue images were used for the classification. The class-imbalanced dataset consisted of 372 instances of cancer, 141 instances of OPMDs, and 1,297 instances of noncancerous lesions. The EfficientNet model was used as the feature extraction model for classification. Mosaic data augmentation, soft labeling, and curriculum learning (CL) were employed to improve the classification performance of the convolutional neural network. RESULTS: Utilizing a mosaic-augmented dataset in conjunction with CL, the final model achieved an accuracy rate of 0.9444, surpassing conventional oversampling and weight balancing methods. The relative precision improvement rate for the minority class OPMD was 21.2%, while the relative [Formula: see text] score improvement rate of OPMD was 4.9%. CONCLUSIONS: The present study demonstrates that the integration of mosaic-based soft labeling and curriculum learning improves the classification performance of tongue lesions compared to previous methods, establishing a foundation for future research on effectively learning from imbalanced data.

Quantification of Plasma Dopamine in Depressed Patients Using Silver-Enriched Silicon Nanowires as SERS-Active Substrates.

A decrease in the levels of dopamine (DA)─a key catecholamine biomarker for major depressive disorder─highlights the need for quantitative analysis of biological fluids to aid in the early diagnosis of diverse neuropsychiatric disorders. This study developed silicon nanowires enriched with silver nanoparticles to serve as a surface-enhanced Raman scattering (SERS) substrate to enable precise and sensitive quantification of blood plasma DA levels in humans. The silver-enriched silicon nanowires (SiNWs@Ag) yielded flower-like assemblies with densely populated SERS "hot spots," allowing sensitive DA detection. By correlating DA concentration with Raman intensity at 1156 cm-1, the plasma DA levels in treatment-naïve patients with major depression (n = 18) were 2 orders of magnitude lower than those in healthy controls (n = 18) (6.56 × 10-10 M vs 1.43 × 10-8 M). The plasma DA concentrations differed significantly between the two groups (two-tailed p = 5.77×10-7), highlighting a distinct demarcation between depression patients and healthy controls. Furthermore, the SiNWs@Ag substrate effectively differentiated between DA and norepinephrine (NE) in mixtures at nanomolar levels, demonstrating its selective detection capability. This study represents the first report on the quantitative detection of DA levels in human blood samples from individuals with major depression using an SERS technique, emphasizing its potential clinical utility in the evaluation and diagnosis of neuropsychiatric disorders.

Chikungunya seroprevalence, force of infection, and prevalence of chronic disability after infection in endemic and epidemic settings: a systematic review, meta-analysis, and modelling study.

BACKGROUND: Chikungunya is an arboviral disease transmitted by Aedes aegypti and Aedes albopictus mosquitoes with a growing global burden linked to climate change and globalisation. We aimed to estimate chikungunya seroprevalence, force of infection (FOI), and prevalence of related chronic disability and hospital admissions in endemic and epidemic settings. METHODS: In this systematic review, meta-analysis, and modelling study, we searched PubMed, Ovid, and Web of Science for articles published from database inception until Sept 26, 2022, for prospective and retrospective cross-sectional studies that addressed serological chikungunya virus infection in any geographical region, age group, and population subgroup and for longitudinal prospective and retrospective cohort studies with data on chronic chikungunya or hospital admissions in people with chikungunya. We did a systematic review of studies on chikungunya seroprevalence and fitted catalytic models to each survey to estimate location-specific FOI (ie, the rate at which susceptible individuals acquire chikungunya infection). We performed a meta-analysis to estimate the proportion of symptomatic patients with laboratory-confirmed chikungunya who had chronic chikungunya or were admitted to hospital following infection. We used a random-effects model to assess the relationship between chronic sequelae and follow-up length using linear regression. The systematic review protocol is registered online on PROSPERO, CRD42022363102. FINDINGS: We identified 60 studies with data on seroprevalence and chronic chikungunya symptoms done across 76 locations in 38 countries, and classified 17 (22%) of 76 locations as endemic settings and 59 (78%) as epidemic settings. The global long-term median annual FOI was 0·007 (95% uncertainty interval [UI] 0·003-0·010) and varied from 0·0001 (0·00004-0·0002) to 0·113 (0·07-0·20). The highest estimated median seroprevalence at age 10 years was in south Asia (8·0% [95% UI 6·5-9·6]), followed by Latin America and the Caribbean (7·8% [4·9-14·6]), whereas median seroprevalence was lowest in the Middle East (1·0% [0·5-1·9]). We estimated that 51% (95% CI 45-58) of people with laboratory-confirmed symptomatic chikungunya had chronic disability after infection and 4% (3-5) were admitted to hospital following infection. INTERPRETATION: We inferred subnational heterogeneity in long-term average annual FOI and transmission dynamics and identified both endemic and epidemic settings across different countries. Brazil, Ethiopia, Malaysia, and India included both endemic and epidemic settings. Long-term average annual FOI was higher in epidemic settings than endemic settings. However, long-term cumulative incidence of chikungunya can be similar between large outbreaks in epidemic settings with a high FOI and endemic settings with a relatively low FOI. FUNDING: International Vaccine Institute.

Mapping the incidence rate of typhoid fever in sub-Saharan Africa.

BACKGROUND: With more than 1.2 million illnesses and 29,000 deaths in sub-Saharan Africa in 2017, typhoid fever continues to be a major public health problem. Effective control of the disease would benefit from an understanding of the subnational geospatial distribution of the disease incidence. METHOD: We collated records of the incidence rate of typhoid fever confirmed by culture of blood in Africa from 2000 to 2022. We estimated the typhoid incidence rate for sub-Saharan Africa on 20 km × 20 km grids by exploring the association with geospatial covariates representing access to improved water and sanitation, health conditions of the population, and environmental conditions. RESULTS: We identified six published articles and one pre-print representing incidence rate estimates in 22 sites in 2000-2022. Estimated incidence rates showed geospatial variation at sub-national, national, and regional levels. The incidence rate was high in Western and Eastern African subregions followed by Southern and Middle African subregions. By age, the incidence rate was highest among 5-14 yo followed by 2-4 yo, > 14 yo, and 0-1 yo. When aggregated across all age classes and grids that comprise each country, predicted incidence rates ranged from 43.7 (95% confidence interval: 0.6 to 591.2) in Zimbabwe to 2,957.8 (95% CI: 20.8 to 4,245.2) in South Sudan per 100,000 person-years. Sub-national heterogeneity was evident with the coefficient of variation at the 20 km × 20 km grid-level ranging from 0.7 to 3.3 and was generally lower in high-incidence countries and widely varying in low-incidence countries. CONCLUSION: Our study provides estimates of 20 km × 20 km incidence rate of typhoid fever across sub-Saharan Africa based on data collected from 2000 through 2020. Increased understanding of the subnational geospatial variation of typhoid fever in Africa may inform more effective intervention programs by better targeting resources to heterogeneously disturbed disease risk.

Distinct spatiotemporal patterns of cortical thinning in Alzheimer's disease-type cognitive impairment and subcortical vascular cognitive impairment.

Previous studies on Alzheimer's disease-type cognitive impairment (ADCI) and subcortical vascular cognitive impairment (SVCI) has rarely explored spatiotemporal heterogeneity. This study aims to identify distinct spatiotemporal cortical atrophy patterns in ADCI and SVCI. 1,338 participants (713 ADCI, 208 SVCI, and 417 cognitively unimpaired elders) underwent brain magnetic resonance imaging (MRI), amyloid positron emission tomography, and neuropsychological tests. Using MRI, this study measures cortical thickness in five brain regions (medial temporal, inferior temporal, posterior medial parietal, lateral parietal, and frontal areas) and utilizes the Subtype and Stage Inference (SuStaIn) model to predict the most probable subtype and stage for each participant. SuStaIn identifies two distinct cortical thinning patterns in ADCI (medial temporal: 65.8%, diffuse: 34.2%) and SVCI (frontotemporal: 47.1%, parietal: 52.9%) patients. The medial temporal subtype of ADCI shows a faster decline in attention, visuospatial, visual memory, and frontal/executive domains than the diffuse subtype (p-value < 0.01). However, there are no significant differences in longitudinal cognitive outcomes between the two subtypes of SVCI. Our study provides valuable insights into the distinct spatiotemporal patterns of cortical thinning in patients with ADCI and SVCI, suggesting the potential for individualized therapeutic and preventive strategies to improve clinical outcomes.

Atypical formations of gintonin lysophosphatidic acids as new materials and their beneficial effects on degenerative diseases.

Fresh ginseng is prone to spoilage due to its high moisture content. For long-term storage, most fresh ginsengs are dried to white ginseng (WG) or steamed for hours at high temperature/pressure and dried to form Korean Red ginseng (KRG). They are further processed for ginseng products when subjected to hot water extraction/concentration under pressure. These WG or KRG preparation processes affect ginsenoside compositions and also other ginseng components, probably during treatments like steaming and drying, to form diverse bioactive phospholipids. It is known that ginseng contains high amounts of gintonin lysophosphatidic acids (LPAs). LPAs are simple lipid-derived growth factors in animals and humans and act as exogenous ligands of six GTP-binding-protein coupled LPA receptor subtypes. LPAs play diverse roles ranging from brain development to hair growth in animals and humans. LPA-mediated signaling pathways involve various GTP-binding proteins to regulate downstream pathways like [Ca2+]i transient induction. Recent studies have shown that gintonin exhibits anti-Alzheimer's disease and anti-arthritis effects in vitro and in vivo mediated by gintonin LPAs, the active ingredients of gintonin, a ginseng-derived neurotrophin. However, little is known about how gintonin LPAs are formed in high amounts in ginseng compared to other herbs. This review introduces atypical or non-enzymatic pathways under the conversion of ginseng phospholipids into gintonin LPAs during steaming and extraction/concentration processes, which exert beneficial effects against degenerative diseases, including Alzheimer's disease and arthritis in animals and humans via LPA receptors.