Disease progression, survival, and molecular disparities in Black and White patients with endometrioid endometrial carcinoma in real-world registries and GOG/NRG oncology randomized phase III clinical trials.

OBJECTIVE: Investigate racial disparities in outcomes and molecular features in Black and White patients with endometrioid endometrial carcinoma (EEC). METHODS: Black and White patients diagnosed with EEC who underwent hysterectomy ± adjuvant treatment in SEER, National Cancer Database (NCDB), the Genomics Evidence Neoplasia Information Exchange (GENIE) project (v.13.0), and eight NCI-sponsored randomized phase III clinical trials (RCTs) were studied. Hazard ratio (HR) and 95% confidence interval (CI) were estimated for cancer-related death (CRD), non-cancer death (NCD), and all-cause death. RESULTS: Black (n = 4397) vs. White (n = 47,959) patients in SEER had a HR (95% CI) of 2.04 (1.87-2.23) for CRD and 1.22 (1.09-1.36) for NCD. In NCDB, the HR (95% CI) for death in Black (n = 13,468) vs. White (n = 155,706) patients was 1.52 (1.46-1.58) dropping to 1.29 (1.23-1.36) after propensity-score matching for age, comorbidity, income, insurance, grade, stage, LVSI, and treatment. In GENIE, Black (n = 109) vs. White (n = 1780) patients had fewer PTEN, PIK3R1, FBXW7, NF1, mTOR, CCND1, and PI3K-pathway-related gene mutations. In contrast, TP53 and DNA-repair-related gene mutation frequency as well as tumor mutational burden-high status were similar in Black and White patients. In RCTs, Black (n = 187) vs. White (n = 2877) patients were more likely to have advanced or recurrent disease, higher grade, worse performance status and progressive disease. Risk of death in Black vs. White patients in RCTs was 2.19 (1.77-2.71) persisting to 1.32 (1.09-1.61) after matching for grade, stage, and treatment arm while balancing age and performance status. CONCLUSIONS: Differences exist in clinical presentation, outcomes, and molecular features in Black vs. White patients with EEC in real-world registries and RCTs. Targeted-drug development, strategies to modify social determinants, and diverse inclusion in RCTs are approaches to reduce disparities.

ß-Phase Yb5Sb3Hx: Magnetic and Thermoelectric Properties Traversing from an Electride to a Semiconductor.

An electride is a compound that contains a localized electron in an empty crystallographic site. This class of materials has a wide range of applications, including superconductivity, batteries, photonics, and catalysis. Both polymorphs of Yb5Sb3 (the orthorhombic Ca5Sb3F structure type (ß phase) and hexagonal Mn5Si3 structure type (α phase)) are known to be electrides with electrons localized in 0D tetrahedral cavities and 1D octahedral chains, respectively. In the case of the orthorhombic ß phase, an interstitial H can occupy the 0D tetrahedral cavity, accepting the anionic electron that would otherwise occupy the site, providing the formula of Yb5Sb3Hx. DFT computations show that the hexagonal structure is energetically favored without hydrogen and that the orthorhombic structure is more stable with hydrogen. Polycrystalline samples of orthorhombic ß phase Yb5Sb3Hx (x = 0.25, 0.50, 0.75, 1.0) were synthesized, and both PXRD lattice parameters and 1H MAS NMR were used to characterize H composition. Magnetic and electronic transport properties were measured to characterize the transition from the electride (semimetal) to the semiconductor. Magnetic susceptibility measurements indicate a magnetic moment that can be interpreted as resulting from either the localized antiferromagnetically coupled electride or the presence of a small amount of Yb3+. At lower H content (x = 0.25, 0.50), a low charge carrier mobility consistent with localized electride states is observed. In contrast, at higher H content (x = 0.75, 1.0), a high charge carrier mobility is consistent with free electrons in a semiconductor. All compositions show low thermal conductivity, suggesting a potentially promising thermoelectric material if charge carrier concentration can be fine-tuned. This work provides an understanding of the structure and electronic properties of the electride and semiconductor, Yb5Sb3Hx, and opens the door to the interstitial design of electrides to tune thermoelectric properties.

ProteoMixture: A cell type deconvolution tool for bulk tissue proteomic data.

Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations, and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and credentialed using transcript-level data alone. To estimate cell admixture using protein abundance data, we analyzed proteome and transcriptome data generated from contrived admixtures of tumor, stroma, and immune cell models or those selectively harvested from the tissue microenvironment by laser microdissection from high grade serous ovarian cancer (HGSOC) tumors. Co-quantified transcripts and proteins performed similarly to estimate stroma and immune cell admixture (r ≥ 0.63) in two commonly used deconvolution algorithms, ESTIMATE or ConsensusTME. We further developed and optimized protein-based signatures estimating cell admixture proportions and benchmarked these using bulk tumor proteomic data from over 150 patients with HGSOC. The optimized protein signatures supporting cell type proportion estimates from bulk tissue proteomic data are available at https://lmdomics.org/ProteoMixture/.

Non-Coding RNAs Potentially Involved in Pyrethroid Resistance of Anopheles funestus Population in Western Kenya.

Backgrounds: The resurgence of Anopheles funestus, a dominant vector of human malaria in western Kenya was partly attributed to insecticide resistance. However, evidence on the molecular basis of pyrethroid resistance in western Kenya is limited. Noncoding RNAs (ncRNAs) form a vast class of RNAs that do not code for proteins and are ubiquitous in the insect genome. Here, we demonstrated that multiple ncRNAs could play a potential role in An. funestusresistance to pyrethroid in western Kenya. Materials and Methods: Anopheles funestus mosquitoes were sampled by aspiration methods in Bungoma, Teso, Siaya, Port Victoria and Kombewa in western Kenya. The F1 progenies were exposed to deltamethrin (0.05%), permethrin (0.75%), DDT (4%) and pirimiphos-methyl (0.25%) following WHO test guidelines. A synergist assay using piperonyl butoxide (PBO) (4%) was conducted to determine cytochrome P450s' role in pyrethroid resistance. RNA-seq was conducted on a combined pool of specimens that were resistant and unexposed, and the results were compared with those of the FANG susceptible strain. This approach aimed to uncover the molecular mechanisms underlying pyrethroid resistance. Results: Pyrethroid resistance was observed in all the sites with an average mortality rate of 57.6%. Port Victoria had the highest level of resistance to permethrin (MR=53%) and deltamethrin (MR=11%) pyrethroids. Teso had the lowest level of resistance to permethrin (MR=70%) and deltamethrin (MR=87%). Resistance to DDT was observed only in Kombewa (MR=89%) and Port Victoria (MR=85%). A full susceptibility to P-methyl (0.25%) was observed in all the sites. PBO synergist assay revealed high susceptibility (>98%) to the pyrethroids in all the sites except for Port Victoria (MR=96%, n=100). Whole transcriptomic analysis showed that most of the gene families associated with pyrethroid resistance comprised non-coding RNAs (67%), followed by imipenemase (10%), cytochrome P450s (6%), cuticular proteins (5%), olfactory proteins (4%), glutathione S-transferases (3%), UDP-glycosyltransferases (2%), ATP-binding cassettes (2%) and carboxylesterases(1%). Conclusions: This study unveils the molecular basis of insecticide resistance in An. funestus in western Kenya, highlighting for the first time the potential role of non-coding RNAs in pyrethroid resistance. Targeting non-coding RNAs for intervention development could help in insecticide resistance management.

Proteogenomic analysis of enriched HGSOC tumor epithelium identifies prognostic signatures and therapeutic vulnerabilities.

We performed a deep proteogenomic analysis of bulk tumor and laser microdissection enriched tumor cell populations from high-grade serous ovarian cancer (HGSOC) tissue specimens spanning a broad spectrum of purity. We identified patients with longer progression-free survival had increased immune-related signatures and validated proteins correlating with tumor-infiltrating lymphocytes in 65 tumors from an independent cohort of HGSOC patients, as well as with overall survival in an additional 126 HGSOC patient cohort. We identified that homologous recombination deficient (HRD) tumors are enriched in pathways associated with metabolism and oxidative phosphorylation that we validated in independent patient cohorts. We further identified that polycomb complex protein BMI-1 is elevated in HR proficient (HRP) tumors, that elevated BMI-1 correlates with poor overall survival in HRP but not HRD HGSOC patients, and that HRP HGSOC cells are uniquely sensitive to BMI-1 inhibition.

Survival disparities in non-Hispanic Black and White cervical cancer patients vary by histology and are largely explained by modifiable factors.

PURPOSE: We investigated racial disparities in survival by histology in cervical cancer and examined the factors contributing to these disparities. METHODS: Non-Hispanic Black and non-Hispanic White (hereafter known as Black and White) patients with stage I-IV cervical carcinoma diagnosed between 2004 and 2017 in the National Cancer Database were studied. Survival differences were compared using Cox modeling to estimate hazard ratio (HR) or adjusted HR (AHR) and 95% confidence interval (CI). The contribution of demographic, socioeconomic and clinical factors to the Black vs White differences in survival was estimated after applying propensity score weighting in patients with squamous cell carcinoma (SCC) or adenocarcinoma (AC). RESULTS: This study included 10,111 Black and 43,252 White patients with cervical cancer. Black patients had worse survival than White cervical cancer patients (HR = 1.40, 95% CI = 1.35-1.45). Survival disparities between Black and White patients varied significantly by histology (HR = 1.20, 95% CI = 1.15-1.24 for SCC; HR = 2.32, 95% CI = 2.12-2.54 for AC, interaction p < 0.0001). After balancing the selected demographic, socioeconomic and clinical factors, survival in Black vs. White patients was no longer different in those with SCC (AHR = 1.01, 95% CI 0.97-1.06) or AC (AHR = 1.09, 95% CI = 0.96-1.24). In SCC, the largest contributors to survival disparities were neighborhood income and insurance. In AC, age was the most significant contributor followed by neighborhood income, insurance, and stage. Diagnosis of AC (but not SCC) at ≥65 years old was more common in Black vs. White patients (26% vs. 13%, respectively). CONCLUSIONS: Histology matters in survival disparities and diagnosis at ≥65 years old between Black and White cervical cancer patients. These disparities were largely explained by modifiable factors.

Association of brain functional connectivity with neurodevelopmental outcomes in healthy full-term newborns.

OBJECTIVE: To study the association between neurodevelopmental outcomes and functional brain connectivity (FBC) in healthy term infants. METHODS: This is a retrospective study of prospectively collected High-density electroencephalography (HD-EEG) from newborns within 72 hours from birth. Developmental assessments were performed at two years of age using the Bayley Scales of Infant Development-III (BSID-III) measuring cognitive, language, motor, and socio-emotional scores. The FBC was calculated using phase synchronization analysis of source signals in delta, theta, alpha, beta, and gamma frequency bands and its association with neurodevelopmental score was assessed with stepwise regression. RESULTS: 47/163 had both HD-EEG and BSID-III scores. The FBC of frontal region was associated with cognitive score in the theta band (corrected p, regression coefficients range: p < 0.01, 1.66-1.735). Language scores were significantly associated with connectivity in all frequency bands, predominantly in the left hemisphere (p < 0.01, -2.74-2.40). The FBC of frontal and occipital brain regions of both hemispheres was related to motor score and socio-emotional development in theta, alpha, and gamma frequency bands (p < 0.01, -2.16-2.97). CONCLUSIONS: Functional connectivity of higher-order processing is already present at term age. SIGNIFICANCE: The FBC might be used to guide interventions for optimizing subsequent neurodevelopment even in low-risk newborns.

SAX-7/L1CAM acts with the adherens junction proteins MAGI-1, HMR-1/Cadherin, and AFD-1/Afadin to promote glial-mediated dendrite extension.

Adherens junctions (AJs) are a fundamental organizing structure for multicellular life. Although AJs are studied mainly in epithelia, their core function - stabilizing cell contacts by coupling adhesion molecules to the cytoskeleton - is important in diverse tissues. We find that two C. elegans sensory neurons, URX and BAG, require conserved AJ proteins for dendrite morphogenesis. We previously showed that URX and BAG dendrites attach to the embryonic nose via the adhesion molecule SAX-7/L1CAM, acting both in neurons and glia, and then extend by stretch during embryo elongation. Here, we find that a PDZ-binding motif (PB) in the SAX-7 cytoplasmic tail acts with other interaction motifs to promote dendrite extension. Using pull-down assays, we find that the SAX-7 PB binds the multi-PDZ scaffolding protein MAGI-1, which bridges it to the cadherin-catenin complex protein HMP-2/ß-catenin. Using cell-specific rescue and depletion, we find that both MAGI-1 and HMR-1/Cadherin act in glia to non-autonomously promote dendrite extension. Double mutant analysis indicates that each protein can act independently of SAX-7, suggesting a multivalent adhesion complex. The SAX-7 PB motif also binds AFD-1/Afadin, loss of which further enhances sax-7 BAG dendrite defects. As MAGI-1, HMR-1, and AFD-1 are all found in epithelial AJs, we propose that an AJ-like complex in glia promotes dendrite extension.

Racial, ethnic and country of origin disparities in aggressive endometrial cancer histologic subtypes.

OBJECTIVE: This study investigated the risk of an aggressive endometrial cancer (EC) diagnosis by race, ethnicity, and country of origin to further elucidate histologic disparities in non-Hispanic Black (NHB), Hispanic, Asian/Pacific Islander (API), American Indian/Alaskan Native (AIAN) vs. non-Hispanic White (NHW) patients, particularly in Hispanic or API subgroups. METHODS: Patient diagnosed between 2004 and 2020 with low grade (LG)-endometrioid endometrial cancer (ECC) or an aggressive EC including grade 3 EEC, serous carcinoma, clear cell carcinoma, mixed epithelial carcinoma, or carcinosarcoma in the National Cancer Database were studied. The odds ratio (OR) and 95% confidence interval (CI) for diagnosis of an aggressive EC histology was estimated using logistic modeling. RESULTS: There were 343,868 NHW, 48,897 NHB, 30,013 Hispanic, 15,015 API and 1646 AIAN patients. The OR (95% CI) for an aggressive EC diagnosis was 3.07 (3.01-3.13) for NHB, 1.08 (1.06-1.11) for Hispanic, 1.17 (1.13-1.21) for API and 1.07 (0.96-1.19) for AIAN, relative to NHW patients. Subset analyses by country of origin illustrated the diversity in the OR for an aggressive EC diagnosis among Hispanic (1.18 for Mexican to 1.87 for Dominican), Asian (1.14 Asian Indian-Pakistani to 1.48 Korean) and Pacific Islander (1.00 for Hawaiian to 1.33 for Samoan) descendants. Hispanic, API and AIAN patients were diagnosed 5-years younger that NHW patients, and the risk for an aggressive EC histology were all significantly higher than NHW patients after correcting for age. Insurance status was another independent risk factor for aggressive histology. CONCLUSIONS: Risk of an aggressive EC diagnosis varied by race, ethnicity, and country of origin. NHB patients had the highest risk, followed by Dominican, South/Central American, Cuban, Korean, Thai, Vietnamese, and Filipino descendants.

Mapping three-dimensional intratumor proteomic heterogeneity in uterine serous carcinoma by multiregion microsampling.

BACKGROUND: Although uterine serous carcinoma (USC) represents a small proportion of all uterine cancer cases, patients with this aggressive subtype typically have high rates of chemotherapy resistance and disease recurrence that collectively result in a disproportionately high death rate. The goal of this study was to provide a deeper view of the tumor microenvironment of this poorly characterized uterine cancer variant through multi-region microsampling and quantitative proteomics. METHODS: Tumor epithelium, tumor-involved stroma, and whole "bulk" tissue were harvested by laser microdissection (LMD) from spatially resolved levels from nine USC patient tumor specimens and underwent proteomic analysis by mass spectrometry and reverse phase protein arrays, as well as transcriptomic analysis by RNA-sequencing for one patient's tumor. RESULTS: LMD enriched cell subpopulations demonstrated varying degrees of relatedness, indicating substantial intratumor heterogeneity emphasizing the necessity for enrichment of cellular subpopulations prior to molecular analysis. Known prognostic biomarkers were quantified with stable levels in both LMD enriched tumor and stroma, which were shown to be highly variable in bulk tissue. These USC data were further used in a comparative analysis with a data generated from another serous gynecologic malignancy, high grade serous ovarian carcinoma, and have been added to our publicly available data analysis tool, the Heterogeneity Analysis Portal ( https://lmdomics.org/ ). CONCLUSIONS: Here we identified extensive three-dimensional heterogeneity within the USC tumor microenvironment, with disease-relevant biomarkers present in both the tumor and the stroma. These data underscore the critical need for upfront enrichment of cellular subpopulations from tissue specimens for spatial proteogenomic analysis.

The Economic Effect of Peer Recovery Support Services: A Review of the Literature.

Peer Recovery Support Services (PRSS) have the potential to be an economically valuable intervention. To investigate this potential, we conducted a scoping review to summarize existing research on the economic impact of PRSS. We searched relevant electronic databases for peer-reviewed articles and grey literature between January 2000 and February 2023 that examined an economic outcome related to PRSS. Following a comprehensive search, screening, and full-text evaluation, eight articles were selected for review. The majority of the studies we identified focused on healthcare cost-avoidance. Some studies supported PRSS as a method of avoiding costly medical services, while others had mixed results. Our scoping review revealed limited studies addressing cost savings associated with PRSS and further research on the economic impact of PRSS is warranted.

Deep learning-based segmentation of multisite disease in ovarian cancer.

PURPOSE: To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods. METHODS: A deep learning model for the two most common disease sites of high-grade serous ovarian cancer lesions (pelvis/ovaries and omentum) was developed and compared against the well-established "no-new-Net" framework and unrevised trainee radiologist segmentations. A total of 451 CT scans collected from four different institutions were used for training (n = 276), evaluation (n = 104) and testing (n = 71) of the methods. The performance was evaluated using the Dice similarity coefficient (DSC) and compared using a Wilcoxon test. RESULTS: Our model outperformed no-new-Net for the pelvic/ovarian lesions in cross-validation, on the evaluation and test set by a significant margin (p values being 4 × 10-7, 3 × 10-4, 4 × 10-2, respectively), and for the omental lesions on the evaluation set (p = 1 × 10-3). Our model did not perform significantly differently in segmenting pelvic/ovarian lesions (p = 0.371) compared to a trainee radiologist. On an independent test set, the model achieved a DSC performance of 71 ± 20 (mean ± standard deviation) for pelvic/ovarian and 61 ± 24 for omental lesions. CONCLUSION: Automated ovarian cancer segmentation on CT scans using deep neural networks is feasible and achieves performance close to a trainee-level radiologist for pelvic/ovarian lesions. RELEVANCE STATEMENT: Automated segmentation of ovarian cancer may be used by clinicians for CT-based volumetric assessments and researchers for building complex analysis pipelines. KEY POINTS: • The first automated approach for pelvic/ovarian and omental ovarian cancer lesion segmentation on CT images has been presented. • Automated segmentation of ovarian cancer lesions can be comparable with manual segmentation of trainee radiologists. • Careful hyperparameter tuning can provide models significantly outperforming strong state-of-the-art baselines.

In situ profiling reveals metabolic alterations in the tumor microenvironment of ovarian cancer after chemotherapy.

In this study, we investigated the metabolic alterations associated with clinical response to chemotherapy in patients with ovarian cancer. Pre- and post-neoadjuvant chemotherapy (NACT) tissues from patients with high-grade serous ovarian cancer (HGSC) who had poor response (PR) or excellent response (ER) to NACT were examined. Desorption electrospray ionization mass spectrometry (DESI-MS) was performed on sections of HGSC tissues collected according to a rigorous laparoscopic triage algorithm. Quantitative MS-based proteomics and phosphoproteomics were performed on a subgroup of pre-NACT samples. Highly abundant metabolites in the pre-NACT PR tumors were related to pyrimidine metabolism in the epithelial regions and oxygen-dependent proline hydroxylation of hypoxia-inducible factor alpha in the stromal regions. Metabolites more abundant in the epithelial regions of post-NACT PR tumors were involved in the metabolism of nucleotides, and metabolites more abundant in the stromal regions of post-NACT PR tumors were related to aspartate and asparagine metabolism, phenylalanine and tyrosine metabolism, nucleotide biosynthesis, and the urea cycle. A predictive model built on ions with differential abundances allowed the classification of patients' tumor responses as ER or PR with 75% accuracy (10-fold cross-validation ridge regression model). These findings offer new insights related to differential responses to chemotherapy and could lead to novel actionable targets.

Automated imaging and identification of proteoforms directly from ovarian cancer tissue.

The molecular identification of tissue proteoforms by top-down mass spectrometry (TDMS) is significantly limited by throughput and dynamic range. We introduce AutoPiMS, a single-ion MS based multiplexed workflow for top-down tandem MS (MS2) directly from tissue microenvironments in a semi-automated manner. AutoPiMS directly off human ovarian cancer sections allowed for MS2 identification of 73 proteoforms up to 54 kDa at a rate of <1 min per proteoform. AutoPiMS is directly interfaced with multifaceted proteoform imaging MS data modalities for the identification of proteoform signatures in tumor and stromal regions in ovarian cancer biopsies. From a total of ~1000 proteoforms detected by region-of-interest label-free quantitation, we discover 303 differential proteoforms in stroma versus tumor from the same patient. 14 of the top proteoform signatures are corroborated by MSI at 20 micron resolution including the differential localization of methylated forms of CRIP1, indicating the importance of proteoform-enabled spatial biology in ovarian cancer.

Brain proteomic atlas of alcohol use disorder in adult males.

Alcohol use disorder (AUD) affects transcriptomic, epigenetic and proteomic expression in several organs, including the brain. There has not been a comprehensive analysis of altered protein abundance focusing on the multiple brain regions that undergo neuroadaptations occurring in AUD. We performed a quantitative proteomic analysis using a liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of human postmortem tissue from brain regions that play key roles in the development and maintenance of AUD, the amygdala (AMG), hippocampus (HIPP), hypothalamus (HYP), nucleus accumbens (NAc), prefrontal cortex (PFC) and ventral tegmental area (VTA). Brain tissues were from adult males with AUD (n = 11) and matched controls (n = 16). Across the two groups, there were >6000 proteins quantified with differential protein abundance in AUD compared to controls in each of the six brain regions. The region with the greatest number of differentially expressed proteins was the AMG, followed by the HYP. Pathways associated with differentially expressed proteins between groups (fold change > 1.5 and LIMMA p < 0.01) were analyzed by Ingenuity Pathway Analysis (IPA). In the AMG, adrenergic, opioid, oxytocin, GABA receptor and cytokine pathways were among the most enriched. In the HYP, dopaminergic signaling pathways were the most enriched. Proteins with differential abundance in AUD highlight potential therapeutic targets such as oxytocin, CSNK1D (PF-670462), GABAB receptor and opioid receptors and may lead to the identification of other potential targets. These results improve our understanding of the molecular alterations of AUD across brain regions that are associated with the development and maintenance of AUD. Proteomic data from this study is publicly available at www.lmdomics.org/AUDBrainProteomeAtlas/ .

Differences in malaria vector biting behavior and changing vulnerability to malaria transmission in contrasting ecosystems of western Kenya.

BACKGROUND: Designing, implementing, and upscaling of effective malaria vector control strategies necessitates an understanding of when and where transmission occurs. This study assessed the biting patterns of potentially infectious malaria vectors at various hours, locations, and associated human behaviors in different ecological settings in western Kenya. METHODS: Hourly indoor and outdoor catches of human-biting mosquitoes were sampled from 19:00 to 07:00 for four consecutive nights in four houses per village. The human behavior study was conducted via questionnaire surveys and observations. Species within the Anopheles gambiae complex and Anopheles funestus group were distinguished by polymerase chain reaction (PCR) and the presence of Plasmodium falciparum circumsporozoite proteins (CSP) determined by enzyme-linked immunosorbent assay (ELISA). RESULTS: Altogether, 2037 adult female anophelines were collected comprising the An. funestus group (76.7%), An. gambiae sensu lato (22.8%), and Anopheles coustani (0.5%). PCR results revealed that Anopheles arabiensis constituted 80.5% and 79% of the An. gambiae s.l. samples analyzed from the lowland sites (Ahero and Kisian, respectively). Anopheles gambiae sensu stricto (hereafter An. gambiae) (98.1%) was the dominant species in the highland site (Kimaeti). All the An. funestus s.l. analyzed belonged to An. funestus s.s. (hereafter An. funestus). Indoor biting densities of An. gambiae s.l. and An. funestus exceeded the outdoor biting densities in all sites. The peak biting occurred in early morning between 04:30 and 06:30 in the lowlands for An. funestus both indoors and outdoors. In the highlands, the peak biting of An. gambiae occurred between 01:00 and 02:00 indoors. Over 50% of the study population stayed outdoors from 18:00 to 22:00 and woke up at 05:00, coinciding with the times when the highest numbers of vectors were collected. The sporozoite rate was higher in vectors collected outdoors, with An. funestus being the main malaria vector in the lowlands and An. gambiae in the highlands. CONCLUSION: This study shows heterogeneity of anopheline distribution, high outdoor malaria transmission, and early morning peak biting activity of An. funestus when humans are not protected by bednets in the lowland sites. Additional vector control efforts targeting the behaviors of these vectors, such as the use of non-pyrethroids for indoor residual spraying and spatial repellents outdoors, are needed.

A sex-specific switch in a single glial cell patterns the apical extracellular matrix.

Apical extracellular matrix (aECM) constitutes the interface between every tissue and the outside world. It is patterned into diverse tissue-specific structures through unknown mechanisms. Here, we show that a male-specific genetic switch in a single C. elegans glial cell patterns the overlying aECM from a solid sheet to an ∼200 nm pore, thus allowing a male sensory neuron to access the environment. Using cell-specific genetic sex reversal, we find that this switch reflects an inherent sex difference in the glial cell that is independent of the sex identity of the surrounding neurons. Through candidate and unbiased genetic screens, we find that this glial sex difference is controlled by factors shared with neurons (mab-3, lep-2, and lep-5) as well as previously unidentified regulators whose effects may be glia specific (nfya-1, bed-3, and jmjd-3.1). The switch results in male-specific glial expression of a secreted Hedgehog-related protein, GRL-18, that we discover localizes to transient nanoscale rings at sites where aECM pores will form. Using electron microscopy, we find that blocking male-specific gene expression in glia prevents pore formation, whereas forcing male-specific glial gene expression induces an ectopic pore. Thus, a switch in gene expression in a single cell is necessary and sufficient to pattern aECM into a specific structure. Our results highlight that aECM is not a simple homogeneous meshwork, but instead is composed of discrete local features that reflect the identity of the underlying cells.