Abnormal resting-state functional connectivity of hippocampal subregions in type 2 diabetes mellitus-associated cognitive decline.

Objective: Type 2 diabetes mellitus (T2DM) over time predisposes to inflammatory responses and abnormalities in functional brain networks that damage learning, memory, or executive function. The hippocampus is a key region often reporting connectivity abnormalities in memory disorders. Here, we investigated peripheral inflammatory responses and resting-state functional connectivity (RSFC) changes characterized of hippocampal subregions in type 2 diabetes-associated cognitive decline (T2DACD). Methods: The study included 16 patients with T2DM, 16 patients with T2DACD and 25 healthy controls (HCs). Subjects were assessed for cognitive performance, tested for the expression of inflammatory factors IL-6, IL-10 and TNF-α in peripheral serum, underwent resting-state functional magnetic resonance imaging scans, and analyzed for RSFC using the hippocampal subregions as seeds. We also calculated the correlation between cognitive performance and RSFC of hippocampal subregion, and analyzed the significantly altered RSFC values of T2DACD for Receiver Operating Characteristic (ROC) analysis. Results: T2DACD patients showed a decline in their ability to complete cognitive assessment scales and experimental paradigms, and T2DM did not show abnormal cognitive performance. IL-6 expression was increased in peripheral serum in both T2DACD and T2DM. Compared with HCs, T2DACD showed abnormalities RSFC of the left anterior hippocampus with left precentral gyrus and left angular gyrus. T2DM showed abnormalities RSFC of the left middle hippocampus with right medial frontal gyrus, right anterior and middle hippocampus with left precuneus, left anterior hippocampus with right precuneus and right posterior middle temporal gyrus. Compared with T2DM, T2DACD showed abnormalities RSFC of the left posterior hippocampus and right middle hippocampus with left precuneus. In addition, RSFC in the left posterior hippocampus with left precuneus of T2DACD was positively correlated with Flanker conflict response time (r=0.766, P=0.001). In the ROC analysis, the significantly altered RSFC values of T2DACD achieved significant performance. Conclusions: T2DACD showed a significant decrease in attentional inhibition and working memory, peripheral pro-inflammatory response increased, and abnormalities RSFC of the hippocampal subregions with default mode network and sensory-motor network. T2DM did not show a significant cognitive decline, but peripheral pro-inflammatory response increased and abnormalities RSFC of the hippocampus subregions occurred in the brain. In addition, the left precuneus may be a key brain region in the conversion of T2DM to T2DACD. The results of this study may provide a basis for the preliminary diagnosis of T2DACD.

Abnormal developmental of hippocampal subfields and amygdalar subnuclei volumes in young adults with heavy cannabis use: A three-year longitudinal study.

BACKGROUND: Differences in the volumes of the hippocampus and amygdala have consistently been observed between young adults with heavy cannabis use relative to their non-using counterparts. However, it remains unclear whether the subfields of these functionally and structurally heterogenous regions exhibit similar patterns of change in young adults with long-term heavy cannabis use disorder (CUD). OBJECTIVES: This study aims to investigate the effects of long-term heavy cannabis use in young adults on the subregional structures of the hippocampus and amygdala, as well as their longitudinal alterations. METHODS: The study sample comprised 20 young adults with heavy cannabis use and 22 matched non-cannabis using healthy volunteers. All participants completed the Cannabis Use Disorder Identification Test (CUDIT) and underwent two T1-structural magnetic resonance imaging (MRI) scans, one at baseline and another at follow-up 3 years later. The amygdala, hippocampus, and their subregions were segmented on T1-weighted anatomical MRI scans, using a previously validated procedure. RESULTS: At baseline, young adults with heavy CUD exhibited significantly larger volumes in several hippocampal (bilateral presubiculum, subiculum, Cornu Ammonis (CA) regions CA1, CA2-CA3, and right CA4-Dentate Gyrus (DG)) and amygdala (bilateral paralaminar nuclei, right medial nucleus, and right lateral nucleus) subregions compared to healthy controls, but these differences were attenuated at follow-up. Longitudinal analysis revealed an accelerated volumetric decrease in these subregions in young adults with heavy CUD relative to controls. Particularly, compared to healthy controls, significant accelerated volume decreases were observed in the right hippocampal subfields of the parasubiculum, subiculum, and CA4-DG. In the amygdala, similar trends of accelerated volumetric decreases were observed in the left central nucleus, right paralaminar nucleus, right basal nucleus, and right accessory basal nucleus. CONCLUSIONS: The current findings suggest that long-term heavy cannabis use impacts maturational process of the amygdala and hippocampus, especially in subregions with high concentrations of cannabinoid type 1 receptors (CB1Rs) and involvement in adult neurogenesis.

Estimating the Size of Populations at High Risk of Malaria in 2 Operational Districts in Cambodia: Household-Based Survey.

BACKGROUND: Cambodia is targeting the elimination of malaria by 2025. The last remaining pockets of malaria in Cambodia are concentrated among populations exposed to forested areas, but the size of these populations is not well understood. To plan for the procurement and distribution of vector-control tools, chemoprophylaxis, and other commodities for malaria prevention and surveillance, robust estimates of the population at greatest risk are required. OBJECTIVE: This study aims to estimate the number of forest-exposed individuals residing in Cambodia's highest-burden operational districts (ODs) in 2 provinces with active malaria transmission. METHODS: In April 2023, a multistage, in-person survey was conducted among residents in the 2 ODs in Cambodia with the highest malaria burden: Sen Monorom in Mondulkiri province and Phnom Srouch in Kampong Speu province. In each OD, 10 villages were randomly selected, and 35 households were randomly selected from each village. To estimate the number of individuals at high risk of malaria-defined as residing within 1 km of a forest or traveling at least once per week to the forest-respondents were asked about the distance from their household to the nearest forested area, and their travel patterns to forested areas. To account for mobility (ie, to avoid double-counting), respondents also provided information on overnight stays at other households in the selected villages in the past month. In the 4 selected villages in Sen Monorom OD where Project BITE forest packs (an intervention in the larger research program) had been distributed prior to the survey, respondents were also asked questions to determine if they had received such a pack, to develop smaller scale "multiplier method" estimates of at-risk individuals in each of those villages. RESULTS: In Sen Monorom, 138 households and 872 individuals were enrolled in the survey, and in Phnom Srouch, 163 households and 844 individuals were enrolled. The estimated percentage of female householders was 49.7% (852/1716) across both ODs; the median age was 22 (IQR 12-37) years in Sen Monorom and 24.5 (IQR 16.0-40.5) years in Phnom Srouch (total age range 3-86). Based on mobility-adjusted survey estimates alone, 32% (280/706; 95% CI 19.9-47.2) of residents in Sen Monorom (an estimated 12,133-20,135 individuals) and 36% (68/198; 95% CI 24.5-45.5) of residents in Phnom Srouch (an estimated 1717-2203 individuals), met risk criteria for forest exposure. Between 125 and 186 individuals were estimated to be at risk in each of the 4 villages where the multiplier method could be applied. CONCLUSIONS: This study provides estimates of the number of individuals potentially at high risk for malaria infection due to forest exposure in 2 ODs in Cambodia. These estimates can support planning for malaria control and elimination efforts. The straightforward methods of household surveys and multipliers should be feasible for many national malaria control programs.

The Effects of Variation in the GABAA Receptor Gene on Anxious Depression are Mediated by the Functional Connectivity Between the Amygdala and Middle Frontal Gyrus.

Background: γ-aminobutyric acid (GABA) and its main receptor, the GABAA receptor, are implicated in major depressive disorder (MDD). Anxious depression (AD) is deemed to be a primary subtype of MDD. The amygdala and the dorsolateral prefrontal cortex (DLPFC) are key brain regions involved in emotional regulation. These regions contain the most GABAA receptors. Although the GABAergic deficit hypothesis of MDD is generally accepted, few studies have demonstrated how GABAA receptor gene polymorphisms affect the functions of specific brain regions, in particular, the amygdala and the DLPFC. Methods: The sample comprised 83 patients with AD, 70 patients with non-anxious depression (NAD), and 62 healthy controls (HC). All participants underwent genotyping for polymorphisms of GABAA receptor subunit genes, followed by a resting-state fMRI scan. The HAMD-17 was used to evaluate the severity of MDD. ANOVA was performed to obtain the difference in the imaging data, GABAA receptor multi-locus genetic profile scores (MGPS), and HAMD-17 scores among three groups, then the significant differences between AD and NAD groups were identified. Mediating effect analysis was used to explore the role of functional connectivity (FC) between the amygdala and DLPFC in the association between the GABAA receptor gene MGPS and AD clinical features. Results: Compared with the NAD group, the AD group had a higher GABAA receptor MGPS. AD patients exhibited a negative correlation between the MGPS and FC of the right centromedial (CM) subregion, and the right middle frontal gyrus (MFG). A negative correlation was also observed between the MGPS and anxiety/somatic symptoms. More importantly, the right CM and right MFG connectivity mediated the association between the GABAA receptor MGPS and anxiety/somatic symptoms in patients with AD. Conclusion: The decreased FC between the right MFG and right CM subregion mediates the association between GABAA receptor MGPS and AD.

High-frequency vibration of beveled crystal plates by using subregional geometric fitting method.

The beveling process is an important process in the manufacturing of resonators, which has a significant impact on the frequency stability of resonators. Without understanding the frequency characteristics of the resonator after beveling, it is impossible to accurately design the beveled resonators. Thus, in order to investigate the vibration characteristics of AT-cut beveled resonators, we investigated the high-frequency vibration in this work by using the subregional geometric fitting method (SGFM) based on Mindlin's plate theory. Quartz crystal plates with nonuniform thicknesses are partitioned into three regions and each region is fitted by using the polynomial functions based on the measured geometric morphology data. The governing equations are obtained based on Mindlin's two-dimensional theory and the coupled vibrations are further solved using the partial differential equation module of COMSOL. In the numerical calculation, we compare the results obtained by the SGFM with those obtained by the global fitting method and the measured data. The accuracy and effectiveness of the SGFM are also verified. It is found that the frequencies obtained by the SGFM are slightly higher than the frequencies obtained by the global fitting method, and the results of SGFM are closer to the measured results. Meanwhile, as the beveling time increases, the frequency increases and the energy trapping effect becomes more significant. The proposed method can significantly improve the computational efficiency of thickness-shear vibration while ensuring accuracy. It is expected to provide a new geometric fitting method for the analysis of beveled crystal resonators.

Ultra-low dose hip CT-based automated measurement of volumetric bone mineral density at proximal femoral subregions.

BACKGROUND: Forty to fifty percent of women and 13%-22% of men experience an osteoporosis-related fragility fracture in their lifetimes. After the age of 50 years, the risk of hip fracture doubles in every 10 years. x-Ray based DXA is currently clinically used to diagnose osteoporosis and predict fracture risk. However, it provides only 2-D representation of bone and is associated with other technical limitations. Thus, alternative methods are needed. PURPOSE: To develop and evaluate an ultra-low dose (ULD) hip CT-based automated method for assessment of volumetric bone mineral density (vBMD) at proximal femoral subregions. METHODS: An automated method was developed to segment the proximal femur in ULD hip CT images and delineate femoral subregions. The computational pipeline consists of deep learning (DL)-based computation of femur likelihood map followed by shape model-based femur segmentation and finite element analysis-based warping of a reference subregion labeling onto individual femur shapes. Finally, vBMD is computed over each subregion in the target image using a calibration phantom scan. A total of 100 participants (50 females) were recruited from the Genetic Epidemiology of COPD (COPDGene) study, and ULD hip CT imaging, equivalent to 18 days of background radiation received by U.S. residents, was performed on each participant. Additional hip CT imaging using a clinical protocol was performed on 12 participants and repeat ULD hip CT was acquired on another five participants. ULD CT images from 80 participants were used to train the DL network; ULD CT images of the remaining 20 participants as well as clinical and repeat ULD CT images were used to evaluate the accuracy, generalizability, and reproducibility of segmentation of femoral subregions. Finally, clinical CT and repeat ULD CT images were used to evaluate accuracy and reproducibility of ULD CT-based automated measurements of femoral vBMD. RESULTS: Dice scores of accuracy (n = 20), reproducibility (n = 5), and generalizability (n = 12) of ULD CT-based automated subregion segmentation were 0.990, 0.982, and 0.977, respectively, for the femoral head and 0.941, 0.970, and 0.960, respectively, for the femoral neck. ULD CT-based regional vBMD showed Pearson and concordance correlation coefficients of 0.994 and 0.977, respectively, and a root-mean-square coefficient of variation (RMSCV) (%) of 1.39% with the clinical CT-derived reference measure. After 3-digit approximation, each of Pearson and concordance correlation coefficients as well as intraclass correlation coefficient (ICC) between baseline and repeat scans were 0.996 with RMSCV of 0.72%. Results of ULD CT-based bone analysis on 100 participants (age (mean ± SD) 73.6 ± 6.6 years) show that males have significantly greater (p < 0.01) vBMD at the femoral head and trochanteric regions than females, while females have moderately greater vBMD (p = 0.05) at the medial half of the femoral neck than males. CONCLUSION: Deep learning, combined with shape model and finite element analysis, offers an accurate, reproducible, and generalizable algorithm for automated segmentation of the proximal femur and anatomic femoral subregions using ULD hip CT images. ULD CT-based regional measures of femoral vBMD are accurate and reproducible and demonstrate regional differences between males and females.

The value of the malignant subregion-based texture analysis in predicting the Ki-67 status in breast cancer.

Objective: To evaluate the value of the malignant subregion-based texture analysis in predicting Ki-67 status in breast cancer. Materials and methods: The dynamic contrast-enhanced magnetic resonance imaging data of 119 histopathologically confirmed breast cancer patients (81 patients with high Ki-67 expression status) from January 2018 to February 2023 in our hospital were retrospectively collected. According to the enhancement curve of each voxel within the tumor, three subregions were divided: washout subregion, plateau subregion, and persistent subregion. The washout subregion and the plateau subregion were merged as the malignant subregion. The texture features of the malignant subregion were extracted using Pyradiomics software for texture analysis. The differences in texture features were compared between the low and high Ki-67 expression cohorts and then the receiver operating characteristic (ROC) curve analysis to evaluate the predictive performance of texture features on Ki-67 expression. Finally, a support vector machine (SVM) classifier was constructed based on differential features to predict the expression level of Ki-67, the performance of the classifier was evaluated using ROC analysis and confirmed using 10-fold cross-validation. Results: Through comparative analysis, 51 features exhibited significant differences between the low and high Ki-67 expression cohorts. Following feature reduction, 5 features were selected to build the SVM classifier, which achieved an area under the ROC curve (AUC) of 0.77 (0.68-0.87) for predicting the Ki-67 expression status. The accuracy, sensitivity, and specificity were 0.76, 0.80, and 0.68, respectively. The average AUC from the 10-fold cross-validation was 0.72 ± 0.14. Conclusion: The texture features of the malignant subregion in breast cancer were potential biomarkers for predicting Ki-67 expression level in breast cancer, which might be used to precisely diagnose and guide the treatment of breast cancer.

Automatic segmentation of medial temporal lobe subregions in multi-scanner, multi-modality MRI of variable quality.

Background: Volumetry of subregions in the medial temporal lobe (MTL) computed from automatic segmentation in MRI can track neurodegeneration in Alzheimer's disease. However, image quality may vary in MRI. Poor quality MR images can lead to unreliable segmentation of MTL subregions. Considering that different MRI contrast mechanisms and field strengths (jointly referred to as "modalities" here) offer distinct advantages in imaging different parts of the MTL, we developed a muti-modality segmentation model using both 7 tesla (7T) and 3 tesla (3T) structural MRI to obtain robust segmentation in poor-quality images. Method: MRI modalities including 3T T1-weighted, 3T T2-weighted, 7T T1-weighted and 7T T2-weighted (7T-T2w) of 197 participants were collected from a longitudinal aging study at the Penn Alzheimer's Disease Research Center. Among them, 7T-T2w was used as the primary modality, and all other modalities were rigidly registered to the 7T-T2w. A model derived from nnU-Net took these registered modalities as input and outputted subregion segmentation in 7T-T2w space. 7T-T2w images most of which had high quality from 25 selected training participants were manually segmented to train the multi-modality model. Modality augmentation, which randomly replaced certain modalities with Gaussian noise, was applied during training to guide the model to extract information from all modalities. To compare our proposed model with a baseline single-modality model in the full dataset with mixed high/poor image quality, we evaluated the ability of derived volume/thickness measures to discriminate Amyloid+ mild cognitive impairment (A+MCI) and Amyloid- cognitively unimpaired (A-CU) groups, as well as the stability of these measurements in longitudinal data. Results: The multi-modality model delivered good performance regardless of 7T-T2w quality, while the single-modality model under-segmented subregions in poor-quality images. The multi-modality model generally demonstrated stronger discrimination of A+MCI versus A-CU. Intra-class correlation and Bland-Altman plots demonstrate that the multi-modality model had higher longitudinal segmentation consistency in all subregions while the single-modality model had low consistency in poor-quality images. Conclusion: The multi-modality MRI segmentation model provides an improved biomarker for neurodegeneration in the MTL that is robust to image quality. It also provides a framework for other studies which may benefit from multimodal imaging.

Revolutionizing breast cancer Ki-67 diagnosis: ultrasound radiomics and fully connected neural networks (FCNN) combination method.

PURPOSE: This study aims to assess the diagnostic value of ultrasound habitat sub-region radiomics feature parameters using a fully connected neural networks (FCNN) combination method L2,1-norm in relation to breast cancer Ki-67 status. METHODS: Ultrasound images from 528 cases of female breast cancer at the Affiliated Hospital of Xiangnan University and 232 cases of female breast cancer at the Affiliated Rehabilitation Hospital of Xiangnan University were selected for this study. We utilized deep learning methods to automatically outline the gross tumor volume and perform habitat clustering. Subsequently, habitat sub-regions were extracted to identify radiomics features and underwent feature engineering using the L1,2-norm. A prediction model for the Ki-67 status of breast cancer patients was then developed using a FCNN. The model's performance was evaluated using accuracy, area under the curve (AUC), specificity (Spe), positive predictive value (PPV), negative predictive value (NPV), Recall, and F1. In addition, calibration curves and clinical decision curves were plotted for the test set to visually assess the predictive accuracy and clinical benefit of the models. RESULT: Based on the feature engineering using the L1,2-norm, a total of 9 core features were identified. The predictive model, constructed by the FCNN model based on these 9 features, achieved the following scores: ACC 0.856, AUC 0.915, Spe 0.843, PPV 0.920, NPV 0.747, Recall 0.974, and F1 0.890. Furthermore, calibration curves and clinical decision curves of the validation set demonstrated a high level of confidence in the model's performance and its clinical benefit. CONCLUSION: Habitat clustering of ultrasound images of breast cancer is effectively supported by the combined implementation of the L1,2-norm and FCNN algorithms, allowing for the accurate classification of the Ki-67 status in breast cancer patients.

Prevalence estimates of Opisthorchis viverrini and Clonorchis sinensis infection in the Greater Mekong subregion: a systematic review and meta-analysis.

BACKGROUND: Opisthorchiasis and clonorchiasis, caused by Opisthorchis viverrini and Clonorchis sinensis, respectively, are significant yet neglected foodborne trematodiases in the Great Mekong Subregion (GMS). Despite the reporting of the prevalence of these human liver flukes in the region over the past decades, there has been a lack of a comprehensive and systematic consolidation of this data. Therefore, we aimed to conduct a thorough systematic review and meta-analysis to synthesize and analyze time-trend prevalence estimates of both O. viverrini and C. sinensis across the GMS for the past 30 years. METHODS: This study undertakes a systematic review using a comprehensive search for published articles in PubMed, EMBASE, Scopus, Cochrane and Thai Journal Online databases until early 2023. The pooled prevalence of O. viverrini and C. sinensis infection was analyzed through a random-effects meta-analysis, with meta-regression analysis used to quantify associations with study characteristics. Sub-group analysis was conducted, whenever comparison data were available, to assess the risk of O. viverrini and C. sinensis infection in each GMS country. Heterogeneity among studies was assessed using the Q statistic and quantified by using the I 2 Index. RESULTS: From a total of 2997 articles, 155 articles comprising 218 datasets and 751,108 participants were included for review. The GMS prevalence of O. viverrini was 21.11% [45,083/260,237; 95% confidence interval (CI): 17.74-24.47%]. Pooled prevalence estimates were highly observed in Laos (34.06%, 95% CI: 26.85-41.26%), followed by Thailand (18.19%, 95% CI: 13.86-22.51%), and Cambodia (10.48%, 95% CI: 5.52-15.45%). Myanmar and Vietnam had limited data sources for calculation. Clonorchis sinensis infection in GMS was 25.33% (95% CI: 18.32-32.34%), with Guangxi, China, exhibiting the highest prevalence rates at 26.89% (95% CI: 18.34-35.43%), while Vietnam had a prevalence rate of 20.30% (95% CI: 9.13-31.47%). O. viverrini prevalence decreased significantly over time, whereas C. sinensis infection appeared to be stable consistently over time in both China and Vietnam. CONCLUSIONS: This comprehensive study, drawing from the largest datasets to date, offers an in-depth systematic prevalence review of human liver flukes in the Greater Mekong Subregion. It underscores the imperative for systematic surveillance, data collection, and the implementation of intervention and control measures for these infectious diseases of poverty.

Intermittent preventive treatment for forest goers by forest malaria workers: an observational study on a key intervention for malaria elimination in Cambodia.

Background: Cambodia targets P. falciparum malaria elimination by 2023 and all human malaria species by 2025, aligning with WHO's Mekong Malaria Elimination program. The Intermittent Preventive Treatment for Forest Goers (IPTf) project aimed at forest-specific malaria elimination. The study aims to pinpoint the main factors driving malaria transmission in Cambodian forests and evaluate the initial implementation and effectiveness of IPTf in accelerating the elimination of malaria by treating and preventing infections among at-risk populations in these areas. Methods: From March 11, 2019, to January 30, 2021, a malaria intervention program took place in isolated forests in Northeast Cambodia. The first phase focused on observing forest goers (FGs) within the forests, documenting their malaria risk. In the second phase, a monthly artesunate-mefloquine IPTf was implemented by trained forest malaria workers who were former FGs conducting interviews, blood collection, and IPTf administration. Findings: Throughout the two-year period, 2198 FGs were involved in 3579 interviews, with 284 in both the observation and intervention phases. Following IPTf implementation, PCR-confirmed malaria prevalence significantly decreased from 2.9% to 0.5% for P. falciparum and from 21.0% to 4.7% for P. vivax. Among the 284 participants tracked through both phases, malaria prevalence fell from 2.5% to 0.3% for P. falciparum and from 22.5% to 3.7% for P. vivax. The intervention phase demonstrated a rapid decline in P. falciparum prevalence among mobile and previously inaccessible populations, while also revealing a higher P. falciparum infection risk associated with activities inaccurately labelled as farming, underscoring the need for customized interventions. Interpretation: The successful implementation of IPTf in Cambodia's remote forests has markedly decreased malaria prevalence among high-risk groups. Cambodia's National Malaria Program has acknowledged this strategy as essential for malaria elimination intervention, endorsing forest-specific approaches to meet the 2025 goal of eradicating all human malaria species in Cambodia. Funding: The study received funding from the French 5% Initiative (Initiative Canal 2-17SANIN205).

[Spatio-temporal Variation in NEP in Ecological Zoning on the Loess Plateau and Its Driving Factors from 2000 to 2021].

Net ecosystem productivity (NEP) is an important index for the quantitative evaluation of carbon sources and sinks in terrestrial ecosystems. Based on MOD17A3 and meteorological data, the vegetation NEP was estimated from 2000 to 2021 in the Loess Plateau (LP) and its six ecological subregions of the LP (loess sorghum gully subregions:A1, A2; loess hilly and gully subregions:B1, B2; sandy land and agricultural irrigation subregion:C; and earth-rock mountain and river valley plain subregion:D). Combined with the terrain, remote sensing, and human activity data, Theil-Sen Median trend analysis, correlation analysis, multiple regression residual analysis, and geographic detector were used, respectively, to explore the spatio-temporal characteristics of NEP and its response mechanism to climate, terrain, and human activity. The results showed that:① On the temporal scale, from 2000 to 2021 the annual mean NEP of the LP region (in terms of C) was 104.62 g·(m2·a)-1. The annual mean NEP for both the whole LP and each of the ecological subregions showed a significant increase trend, and the NEP of the LP increased by 6.10 g·(m2·a)-1 during the study period. The highest growth rate of the NEP was 9.04 g·(m2·a)-1, occurring in the A2 subregion of the loess sorghum gully subregions. The subregion C had the lowest growth rate of 2.74 g·(m2·a)-1. Except for the C subregion, all other ecological subregions (A1, A2, B1, B2, and D) were carbon sinks. ② On the spatial scale, the spatial distribution of annual NEP on the LP was significantly different, with the higher NEP distribution in the southeast of the LP and the lower in the northwest of the LP. The high carbon sink area was mainly distributed in the southern part of the loess sorghum gully subregions, and the carbon source area was mainly distributed in the northern part of the loess sorghum gully subregions and most of the C subregion. The high growth rate was mainly distributed in the central and the southern part of the A2 subregion and the southwest part of the B2 subregion. ③ Human activities had the greatest influence on the temporal variation in NEP in the LP and all the ecological subregions, with the correlation coefficient between human activity data and NEP being above 0.80, and the relative contribution rates of human factors was greater than 50%. The spatial distribution was greatly affected by meteorological factors, among which the precipitation and solar radiation were the main factors affecting the spatial changes in the NEP of the LP. The temporal and spatial variations in the NEP in the LP were influenced by natural and human social factors. To some extent, these results can provide a reference for the terrestrial ecosystem in the LP to reduce emissions and increase sinks and to achieve the goal of double carbon.

Exploring ascomycete diversity in Yunnan II: Introducing three novel species in the suborder Massarineae (Dothideomycetes, Pleosporales) from fern and grasses.

This article presents the results of an ongoing inventory of Ascomycota in Yunnan, China, carried out as part of the research project series "Exploring ascomycete diversity in Yunnan". From over 100 samples collected from diverse host substrates, microfungi have been isolated, identified and are currently being documented. The primary objective of this research is to promote the discovery of novel taxa and explore the ascomycete diversity in the region, utilising a morphology-phylogeny approach. This article represents the second series of species descriptions for the project and introduces three undocumented species found in the families Bambusicolaceae, Dictyosporiaceae and Periconiaceae, belonging to the suborder Massarineae (Pleosporales, Dothideomycetes). These novel taxa exhibit typical morphological characteristics of Bambusicola, Periconia and Trichobotrys, leading to their designation as Bambusicolahongheensis, Periconiakunmingensis and Trichobotryssinensis. Comprehensive multigene phylogenetic analyses were conducted to validate the novelty of these species. The results revealed well-defined clades that are clearly distinct from other related species, providing robust support for their placement within their respective families. Notably, this study unveils the phylogenetic affinity of Trichobotrys within Dictyosporiaceae for the first time. Additionally, the synanamorphism for the genus Trichobotrys is also reported for the first time. Detailed descriptions, illustrations and updated phylogenies of the novel species are provided, and thus presenting a valuable resource for researchers and mycologists interested in the diversity of ascomycetes in Yunnan. By enhancing our understanding of the Ascomycota diversity in this region, this research contributes to the broader field of fungal taxonomy and their phylogenetic understanding.

Subregional thalamic functional connectivity abnormalities and cognitive impairments in first-episode schizophrenia.

BACKGROUND: Previous studies have documented thalamic functional connectivity (FC) abnormalities in schizophrenia, typically examining the thalamus as a whole. The specific link between subregional thalamic FC and cognitive deficits in first-episode schizophrenia (FES) remains unexplored. METHODS: Using data from resting-state functional magnetic resonance imaging, we compared whole-brain FC with thalamic subregions between patients and HCs, and analyzed FC changes in drug-naïve patients separately. We then examined correlations between FC abnormalities with both cognitive impairment and clinical symptoms. RESULTS: A total of 33 FES patients (20 drug-naïve) and 32 age- and sex-matched healthy controls (HCs) were included. Compared to HCs, FES patients exhibited increased FC between specific thalamic subregions and cortical regions, particularly bilateral middle temporal lobe and cuneus gyrus, left medial superior frontal gyrus, and right inferior/superior occipital gyrus. Decreased FC was observed between certain thalamic subregions and the left inferior frontal triangle. These findings were largely consistent in drug-naïve patients. Notably, deficits in social cognition and visual learning in FES patients correlated with increased FC between certain thalamic subregions and cortical regions involving the right superior occipital gyrus and cuneus gyrus. The severity of negative symptoms was associated with increased FC between a thalamic subregion and the left middle temporal gyrus. CONCLUSION: Our findings suggest FC abnormalities between thalamic subregions and cortical areas in FES patients. Increased FC correlated with cognitive deficits and negative symptoms, highlighting the importance of thalamo-cortical connectivity in the pathophysiology of schizophrenia.

Functional connectivity of the amygdala subregions and the antidepressant effects of repeated ketamine infusions in major depressive disorder.

BACKGROUND: Amygdala subregion-based network dysfunction has been determined to be centrally implicated in major depressive disorder (MDD). Little is known about whether ketamine modulates amygdala subarea-related networks. We aimed to investigate the relationships between changes in the resting-state functional connectivity (RSFC) of amygdala subregions and ketamine treatment and to identify important neuroimaging predictors of treatment outcomes. METHODS: Thirty-nine MDD patients received six doses of ketamine (0.5 mg/kg). Depressive symptoms were assessed, and magnetic resonance imaging (MRI) scans were performed before and after treatment. Forty-five healthy controls underwent one MRI scan. Seed-to-voxel RSFC analyses were performed on the amygdala subregions, including the centromedial amygdala (CMA), laterobasal amygdala (LBA), and superficial amygdala subregions. RESULTS: Abnormal RSFC between the left LBA and the left precuneus in MDD patients is related to the therapeutic efficacy of ketamine. There were significant differences in changes in bilateral CMA RSFC with the left orbital part superior frontal gyrus and in changes in the left LBA with the right middle frontal gyrus between responders and nonresponders following ketamine treatment. Moreover, there was a difference in the RSFC of left LBA and the right superior temporal gyrus/middle temporal gyrus (STG/MTG) between responders and nonresponders at baseline, which could predict the antidepressant effect of ketamine on Day 13. CONCLUSIONS: The mechanism by which ketamine improves depressive symptoms may be related to its regulation of RSFC in the amygdala subregion. The RSFC between the left LBA and right STG/MTG may predict the response to the antidepressant effect of ketamine.

Progress towards malaria elimination in the Greater Mekong Subregion: perspectives from the World Health Organization.

Malaria remains a global health challenge, disproportionately affecting vulnerable communities. Despite substantial progress, the emergence of anti-malarial drug resistance poses a constant threat. The Greater Mekong Subregion (GMS), which includes Cambodia, China's Yunnan province, Lao People's Democratic Republic, Myanmar, Thailand, and Viet Nam has been the epicentre for the emergence of resistance to successive generations of anti-malarial therapies. From the perspective of the World Health Organization (WHO), this article considers the collaborative efforts in the GMS, to contain Plasmodium falciparum artemisinin partial resistance and multi-drug resistance and to advance malaria elimination. The emergence of artemisinin partial resistance in the GMS necessitated urgent action and regional collaboration resulting in the Strategy for Malaria Elimination in the Greater Mekong Subregion (2015-2030), advocating for accelerated malaria elimination interventions tailored to country needs, co-ordinated and supported by the WHO Mekong malaria elimination programme. The strategy has delivered substantial reductions in malaria across all GMS countries, with a 77% reduction in malaria cases and a 97% reduction in malaria deaths across the GMS between 2012 and 2022. Notably, China was certified malaria-free by WHO in 2021. Countries' ownership and accountability have been pivotal, with each GMS country outlining its priorities in strategic and annual work plans. The development of strong networks for anti-malarial drug resistance surveillance and epidemiological surveillance was essential. Harmonization of policies and guidelines enhanced collaboration, ensuring that activities were driven by evidence. Challenges persist, particularly in Myanmar, where security concerns have limited recent progress, though an intensification and acceleration plan aims to regain momentum. Barriers to implementation can slow progress and continuing innovation is needed. Accessing mobile and migrant populations is key to addressing remaining transmission foci, requiring effective cross-border collaboration. In conclusion, the GMS has made significant progress towards malaria elimination, particularly in the east where several countries are close to P. falciparum elimination. New and persisting challenges require sustained efforts and continued close collaboration. The GMS countries have repeatedly risen to every obstacle presented, and now is the time to re-double efforts and achieve the 2030 goal of malaria elimination for the region.

Reduced gray matter volume of the hippocampal tail in melancholic depression: evidence from an MRI study.

BACKGROUND: Melancholic depression (MD) is one of the most prevalent and severe subtypes of major depressive disorder (MDD). Previous studies have revealed inconsistent results regarding alterations in grey matter volume (GMV) of the hippocampus and amygdala of MD patients, possibly due to overlooking the complexity of their internal structure. The hippocampus and amygdala consist of multiple and functionally distinct subregions, and these subregions may play different roles in MD. This study aims to investigate the volumetric alterations of each subregion of the hippocampus and amygdala in patients with MD and non-melancholic depression (NMD). METHODS: A total of 146 drug-naïve, first-episode MDD patients (72 with MD and 74 with NMD) and 81 gender-, age-, and education-matched healthy controls (HCs) were included in the study. All participants underwent magnetic resonance imaging (MRI) scans. The subregional segmentation of hippocampus and amygdala was performed using the FreeSurfer 6.0 software. The multivariate analysis of covariance (MANCOVA) was used to detect GMV differences of the hippocampal and amygdala subregions between three groups. Partial correlation analysis was conducted to explore the relationship between hippocampus or amygdala subfields and clinical characteristics in the MD group. Age, gender, years of education and intracranial volume (ICV) were included as covariates in both MANCOVA and partial correlation analyses. RESULTS: Patients with MD exhibited a significantly lower GMV of the right hippocampal tail compared to HCs, which was uncorrelated with clinical characteristics of MD. No significant differences were observed among the three groups in overall and subregional GMV of amygdala. CONCLUSIONS: Our findings suggest that specific hippocampal subregions in MD patients are more susceptible to volumetric alterations than the entire hippocampus. The reduced right hippocampal tail may underlie the unique neuropathology of MD. Future longitudinal studies are required to better investigate the associations between reduced right hippocampal tail and the onset and progression of MD.

Using serological diagnostics to characterize remaining high-incidence pockets of malaria in forest-fringe Cambodia.

BACKGROUND: Over the last decades, the number of malaria cases has drastically reduced in Cambodia. As the overall prevalence of malaria in Cambodia declines, residual malaria transmission becomes increasingly fragmented over smaller remote regions. The aim of this study was to get an insight into the burden and epidemiological parameters of Plasmodium infections on the forest-fringe of Cambodia. METHODS: 950 participants were recruited in the province of Mondulkiri in Cambodia and followed up from 2018 to 2020. Whole-blood samples were processed for Plasmodium spp. identification by PCR as well as for a serological immunoassay. A risk factor analysis was conducted for Plasmodium vivax PCR-detected infections throughout the study, and for P. vivax seropositivity at baseline. To evaluate the predictive effect of seropositivity at baseline on subsequent PCR-positivity, an analysis of P. vivax infection-free survival time stratified by serological status at baseline was performed. RESULTS: Living inside the forest significantly increased the odds of P. vivax PCR-positivity by a factor of 18.3 (95% C.I. 7.7-43.5). Being a male adult was also a significant predictor of PCR-positivity. Similar risk profiles were identified for P. vivax seropositivity. The survival analysis showed that serological status at baseline significantly correlated with subsequent infection. Serology is most informative outside of the forest, where 94.0% (95% C.I. 90.7-97.4%) of seronegative individuals survived infection-free, compared to 32.4% (95% C.I.: 22.6-46.6%) of seropositive individuals. CONCLUSION: This study justifies the need for serological diagnostic assays to target interventions in this region, particularly in demographic groups where a lot of risk heterogeneity persists, such as outside of the forest.

Antigenic strain diversity predicts different biogeographic patterns of maintenance and decline of antimalarial drug resistance.

The establishment and spread of antimalarial drug resistance vary drastically across different biogeographic regions. Though most infections occur in sub-Saharan Africa, resistant strains often emerge in low-transmission regions. Existing models on resistance evolution lack consensus on the relationship between transmission intensity and drug resistance, possibly due to overlooking the feedback between antigenic diversity, host immunity, and selection for resistance. To address this, we developed a novel compartmental model that tracks sensitive and resistant parasite strains, as well as the host dynamics of generalized and antigen-specific immunity. Our results show a negative correlation between parasite prevalence and resistance frequency, regardless of resistance cost or efficacy. Validation using chloroquine-resistant marker data supports this trend. Post discontinuation of drugs, resistance remains high in low-diversity, low-transmission regions, while it steadily decreases in high-diversity, high-transmission regions. Our study underscores the critical role of malaria strain diversity in the biogeographic patterns of resistance evolution.

Drug resistance among strains of the parasites that cause malaria is a growing problem for people relying on antimalarial drugs to protect them from the disease. This phenomenon is global yet exactly how resistance emerges, spreads and persists in a population often differs greatly between regions, which can complicate malaria control projects. For example, discontinuing the use of antimalarials can lead to the frequency of resistant strains declining in an area, such as Africa, but persisting at high levels in others, including Asia and South America. Gaining resistance often leads to parasites becoming less transmissible than other strains. When antimalarials are not used, sensitive strains usually outcompete their resistant counterparts. However, prolonged use of antimalarial drugs tends to eliminate susceptible strains, allowing the previously outcompeted resistant strains to dominate. The local dynamics of antimalarial resistance are also shaped by multiple other factors such as transmission levels (how common the disease is in the region), the type of antimalarial measures used (such as drugs and mosquito nets), or previous immunity the population may have developed to specific strains. While many computational models have been developed to capture these dynamics, they usually fail to include strain diversity ­ a parameter reflecting the number of malaria strains the immune system is exposed to. This parameter is important as parasites need to escape both host immunity and drugs in order to be successful. To address this gap, He, Chaillet, and Labbé created a computational model to investigate how strain diversity, transmission levels and other related factors influence antimalarial resistance. The model was used to explore how the frequency of resistant and susceptible strains changes over time once antimalarial drugs are rolled out and then halted. These analyses show that in areas with both low strain diversity and low transmission levels, susceptible parasites are more likely to be wiped out from the population, leading to a high frequency of resistant strains that persist after drugs are discontinued. However, in high diversity and high transmission regions, susceptible strains can remain in the population. Therefore, when drug treatments are stopped, resistance levels are more likely to drop due to these parasites outcompeting the drug-resistant ones. Overall, this work demonstrates how modelling approaches that include strain diversity can help inform public health decisions aimed at reducing antimalarial resistance. In particular, they can provide important insights into the control strategies that are best suited for a specific region, suggesting that in low transmission areas intensive drug treatment may contribute to resistance. Instead, preventative strategies such as eliminating mosquitos and preventing bites with bed nets may prove more beneficial at reducing transmission rates in such areas.

Functional connectivity changes of the hippocampal subregions in anti-N-methyl-D-aspartate receptor encephalitis.

The hippocampus plays an important role in the pathophysiological mechanism of Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis. Nevertheless, the connection between the resting-state activity of the hippocampal subregions and neuropsychiatric disorders in patients remains unclear. This study aimed to explore the changes in functional connectivity (FC) in the hippocampal subregions of patients with anti-NMDAR encephalitis and its association with clinical symptoms and cognitive performance. Twenty-three patients with anti-NMDAR encephalitis and 23 healthy controls (HC) were recruited. All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans and completed clinical cognitive scales. Based on the Brainnetome Atlas, the rostral (anterior) and caudal (posterior) hippocampi of both the left and right hemispheres were selected as regions of interest (ROIs) for FC analysis. First, a one-sample t-test was used to observe the whole-brain connectivity distribution of hippocampal subregions within the patient and HC groups at a threshold of p < 0.05. The two-sample t-test was used to compare the differences in hippocampal ROIs connectivity between groups, followed by a partial correlation analysis between the FC values of brain regions with statistical differences and clinical variables. This study observed that the distribution of whole-brain functional connectivity in the rostral and caudal hippocampi aligned with the connectivity differences between the anterior and posterior hippocampi. Compared to the HC group, the patients showed significantly decreased FC between the bilateral rostral hippocampus and the left inferior orbitofrontal gyrus and between the right rostral hippocampus and the right cerebellum. However, a significant increase in FC was observed between the right rostral hippocampus and left superior temporal gyrus, the left caudal hippocampus and right superior frontal gyrus, and the right caudal hippocampus and left gyrus rectus. Partial correlation analysis showed that FC between the left inferior orbitofrontal gyrus and the right rostral hippocampus was significantly negatively correlated with the California Verbal Learning Test (CVLT) and Brief Visuospatial Memory Test (BVMT) scores. The FC between the right rostral hippocampus and the left superior temporal gyrus was negatively correlated with BVMT scores. FC abnormalities in the hippocampal subregions of patients with anti-NMDAR encephalitis were associated with cognitive impairment, emotional changes, and seizures. These results may help explain the pathophysiological mechanisms and clinical manifestations of anti-NMDAR encephalitis and NMDAR dysfunction-related diseases such as schizophrenia.