Background: Singapore General Hospital (SGH) is the largest acute tertiary-care hospital in Singapore. Healthcare workers (HCWs) are at risk of acquiring COVID-19 in both the community and workplaces. SGH has a robust exposure management process including prompt contact tracing, immediate ring fencing, lock down of affected cubicles or single room isolation for patient contacts, and home isolation orders for staff contacts of COVID-19 cases during the containment phase of the pandemic. Contacts were also placed on enhanced surveillance with PCR testing on days 1 and 4 as well as daily antigen rapid tests (ARTs) for 10 days after exposure. Here, we describe the characteristic of HCWs with COVID-19 during the third wave of the COVID-19 pandemic. Methods: This retrospective observational study included all SGH HCWs who acquired COVID-19 during the third wave (ie, the 18-week period from September 1 to December 31, 2021) of the COVID-19 pandemic. Univariate analysis was used to compare characteristics of work-associated infection (WAI) and community-acquired infection (CAI) among HCWs. Results: Among a workforce of >10,000 at SGH, 335 HCWs acquired COVID-19 during study period. CAI (exposure to known clusters or household contact) accounted for 111 HCW infections (33.1%). Also, 48 HCWs (14.3%) had a WAI (ie, acquired at their work places where there was no patient contact). Among WAsI, only 5 HCWs had hospital-acquired infection (confirmed by phylogenetic analysis). The sources of exposure for the remaining 176 HCWs were unknown. Weekly incidence of COVID-19 among HCWs was comparable to the epidemiology curve of all cases in Singapore (Fig. 1 and 2). The mean age of HCWs with COVID-19 was 39.6 years, and most were women. At the time of positive SARS-CoV-2 PCR test, 223 HCWs were symptomatic, and 67 (20.0%) of them had comorbidities. Only 16 HCWs (4.8%) required hospitalization, and all recovered fully with no mortality (Table 1). Being female was associated with community COVID-19 acquisition (OR, 4.6, P Conclusions: During the thrid wave of the COVID-19 pandemic, a higher percentage of HCWs at SGH acquired the infection from the community than from the workplace. Safe management measures, such as universal masking, social distancing, and robust exposure management processes including prompt contact tracing and environmental disinfection, can reduce the risk of COVID-19 in the hospital work environment.

Funding: None

Disclosures: None

Sporadic clusters of healthcare-associated coronavirus disease 2019 (COVID-19) occurred despite intense rostered routine surveillance and a highly vaccinated healthcare worker (HCW) population, during a community surge of the severe acute respiratory coronavirus virus 2 (SARS-CoV-2) B.1.617.2 δ (delta) variant. Genomic analysis facilitated timely cluster detection and uncovered additional linkages via HCWs moving between clinical areas and among HCWs sharing a common lunch area, enabling early intervention.

OBJECTIVES/GOALS: To develop a two-staged convolutional neural network to identify the ovary and antral follicles within ovarian ultrasound images and determine its reliability and feasibility compared to conventional techniques in 2D and 3D ultrasonography image analysis. METHODS/STUDY POPULATION: De-identified and archived ultrasonographic images of women across the reproductive spectrum (N=500) will be used in the study. These ultrasound images will be labeled by experienced raters to train a two-staged convolutional neural network (CU-Net). CU-Net will first separate the entire ovary from the background and subsequently identify all antral follicles within the ovary. Following training, the CU-Net will evaluate a second set of independent images (N=100) to determine performance accuracy. Three specialized raters will establish the reliability and feasibility of CU-Net compared to conventional 2D and 3D ovarian ultrasound image analysis methods. RESULTS/ANTICIPATED RESULTS: The labeled training dataset of ovarian ultrasound images is expected to successfully train the CU-Net and allow for accurate identification of the ovary and the total number of antral follicles in the second testing set of ultrasound images. When compared to conventional 2D and 3D ultrasound image analysis methods, CU-Net is expected to have similar accuracy when compared to the gold-standard method (2D-Offline with Grid) and outperform other approaches, such as 2D-Real Time and 3D volume software (VOCAL and Sono-AVC). However, CU-Net is anticipated to be the fastest and most reliable method across users, supporting its clinical feasibility. DISCUSSION/SIGNIFICANCE: This study will immediately translate to providing a standardized platform that can improve the accuracy, reliability, and time demand required for the evaluation of ovarian ultrasounds across users and clinical and research settings.

We study the classical Hermite–Hadamard inequality in the matrix setting. This leads to a number of interesting matrix inequalities such as the Schatten p-norm estimates

$$ \begin{align*}\left(\|A^q\|_p^p + \|B^q\|_p^p\right)^{1/p} \le \|(xA+(1-x)B)^q\|_p+ \|((1-x)A+xB)^q\|_p, \end{align*} $$

$n\times n$

$A,B$

$0<q,x<1$

$X^*X+Y^*Y=XX^*+YY^*=I$

$$ \begin{align*}(X^*AX+Y^*BY)\oplus (Y^*AY+X^*BX) =\frac{1}{2n}\sum_{k=1}^{2n} U_k (A\oplus B)U_k^*, \end{align*} $$

$2n\times 2n$

$U_k$

Disease-related malnutrition is prevalent among older adults; therefore, identifying the modifiable risk factors in the diet is essential for the prevention and management of disease-related malnutrition. The present study examined the cross-sectional association between dietary patterns and malnutrition in Chinese community-dwelling older adults aged ≥65 years in Hong Kong. Dietary patterns, including Diet Quality Index International (DQI-I), Dietary Approaches to Stop Hypertension (DASH), the Mediterranean Diet Score, ‘vegetable–fruit’ pattern, ‘snack–drink–milk product’ pattern and ‘meat–fish’ pattern, were estimated and generated from a validated food frequency questionnaire. Malnutrition was classified according to the modified Global Leadership Initiative on Malnutrition (GLIM) criteria based on two phenotypic components (low body mass index and reduced muscle mass) and one aetiologic component (inflammation/disease burden). The association between the tertile or level of adherence of each dietary pattern and modified GLIM criteria was analysed using adjusted binary logistic regression models. Data of 3694 participants were available (49 % men). Malnutrition was present in 397 participants (10⋅7 %). In men, a higher DQI-I score, a higher ‘vegetable–fruit’ pattern score and a lower ‘meat–fish’ pattern score were associated with a lower risk of malnutrition. In women, higher adherence to the DASH diet was associated with a lower risk of malnutrition. After the Bonferroni correction, the association remained statistically significant only in men for the DQI-I score. To conclude, a higher DQI-I score was associated with a lower risk of malnutrition in Chinese older men. Nutritional strategies for the prevention and management of malnutrition could potentially be targeted on dietary quality.

We obtain several norm and eigenvalue inequalities for positive matrices partitioned into four blocks. The results involve the numerical range $W(X)$ of the off-diagonal block $X$, especially the distance $d$ from $0$ to $W(X)$. A special consequence is an estimate,

$$\begin{eqnarray}\text{diam}\,W\left(\left[\begin{array}{@{}cc@{}}A & X\\ X^{\ast } & B\end{array}\right]\right)-\text{diam}\,W\biggl(\frac{A+B}{2}\biggr)\geq 2d,\end{eqnarray}$$

In bilinguals, language proficiency has been advanced to influence the involvement of domain-general control networks in language selection. We assessed, in university student translators with moderate- to high-second language (L2) proficiency depending on their translation educational level, the functional activity in the key language and control areas (the caudate nucleus, anterior cingulate, and prefrontal cortex), during task- and language-selection in an oral production context. We found that L2 proficiency influenced the relative involvement of our regions of interest during language selection vs domain-general cognitive control processes. While the left middle frontal and left caudate areas were more involved during linguistic than alphanumeric task selection in the low L2 proficiency group, these regions were similarly involved in both tasks in the high-L2 proficiency group. These findings suggest that language selection relies primarily on a network within domain-general cognitive control system with an increase in resource needs when L2 proficiency is low.

Psychotropic medication use and psychiatric symptoms during pregnancy each are associated with adverse neurodevelopmental outcomes in offspring. Commonly, studies considering medication effects do not adequately assess symptoms, nor evaluate children when the effects are believed to occur, the fetal period. This study examined maternal serotonin reuptake inhibitor and polypharmacy use in relation to serial assessments of five indices of fetal neurobehavior and Bayley Scales of Infant Development at 12 months in N = 161 socioeconomically advantaged, non-Hispanic White women with a shared risk phenotype, diagnosed major depressive disorder. On average fetuses showed the expected development over gestation. In contrast, infant average Bayley psychomotor and mental development scores were low (M = 84.10 and M = 89.92, range of normal limits 85–114) with rates of delay more than 2–3 times what would be expected based on this measure's normative data. Controlling for prenatal and postnatal depressive symptoms, prenatal medication effects on neurobehavioral development were largely undetected in the fetus and infant. Mental health care directed primarily at symptoms may not address the additional psychosocial needs of women parenting infants. Speculatively, prenatal serotonin reuptake inhibitor exposure may act as a plasticity rather than risk factor, potentially enhancing receptivity to a nonoptimal postnatal environment in some mother–infant dyads.

We report detections of thermal X-ray line emission and proper motions in the supernova remnant (SNR) RX J1713.7-3946, the prototype of the small class of synchrotron dominated SNRs. Based on deep XMM-Newton observations, we find clear line features including Ne Lyα, Mg Heα, and Si Heα from the central portion of the remnant. The metal abundance ratios suggest that the thermal emission originates from core-collapse SN ejecta arising from a relatively low-mass (≲20 M⊙) progenitor. In addition, using XMM-Newton observations on a 13 yr time interval, we have measured expansion in the southeastern rim to be ~0.75″ yr−1 or ~3500 km s−1 at a distance of 1 kpc. Given this, we derive an upstream density to be ~0.01 cm−3, compatible with the lack of thermal X-rays from the shocked ambient medium. We also estimate the age of the remnant to be ~1200–1600 yr, roughly consistent with the idea that RX J1713.7-3946 is the remnant of SN 393.

To evaluate the appropriateness of the screening strategy for healthcare personnel (HCP) during a hospital-associated Middle East Respiratory Syndrome (MERS) outbreak, we performed a serologic investigation in 189 rRT-PCR–negative HCP exposed and assigned to MERS patients. Although 20%–25% of HCP experienced MERS-like symptoms, none of them showed seroconversion by plaque reduction neutralization test (PRNT).

Infect Control Hosp Epidemiol 2017;38:234–238

The subsurface exploration of other planetary bodies can be used to unravel their geological history and assess their habitability. On Mars in particular, present-day habitable conditions may be restricted to the subsurface. Using a deep subsurface mine, we carried out a program of extraterrestrial analog research – MINe Analog Research (MINAR). MINAR aims to carry out the scientific study of the deep subsurface and test instrumentation designed for planetary surface exploration by investigating deep subsurface geology, whilst establishing the potential this technology has to be transferred into the mining industry. An integrated multi-instrument suite was used to investigate samples of representative evaporite minerals from a subsurface Permian evaporite sequence, in particular to assess mineral and elemental variations which provide small-scale regions of enhanced habitability. The instruments used were the Panoramic Camera emulator, Close-Up Imager, Raman spectrometer, Small Planetary Linear Impulse Tool, Ultrasonic drill and handheld X-ray diffraction (XRD). We present science results from the analog research and show that these instruments can be used to investigate in situ the geological context and mineralogical variations of a deep subsurface environment, and thus habitability, from millimetre to metre scales. We also show that these instruments are complementary. For example, the identification of primary evaporite minerals such as NaCl and KCl, which are difficult to detect by portable Raman spectrometers, can be accomplished with XRD. By contrast, Raman is highly effective at locating and detecting mineral inclusions in primary evaporite minerals. MINAR demonstrates the effective use of a deep subsurface environment for planetary instrument development, understanding the habitability of extreme deep subsurface environments on Earth and other planetary bodies, and advancing the use of space technology in economic mining.